de los Campos, Gustavo; Gianola, Daniel
2007-01-01
Multivariate linear models are increasingly important in quantitative genetics. In high dimensional specifications, factor analysis (FA) may provide an avenue for structuring (co)variance matrices, thus reducing the number of parameters needed for describing (co)dispersion. We describe how FA can be used to model genetic effects in the context of a multivariate linear mixed model. An orthogonal common factor structure is used to model genetic effects under Gaussian assumption, so that the marginal likelihood is multivariate normal with a structured genetic (co)variance matrix. Under standard prior assumptions, all fully conditional distributions have closed form, and samples from the joint posterior distribution can be obtained via Gibbs sampling. The model and the algorithm developed for its Bayesian implementation were used to describe five repeated records of milk yield in dairy cattle, and a one common FA model was compared with a standard multiple trait model. The Bayesian Information Criterion favored the FA model. PMID:17897592
Reid, Jane M; Arcese, Peter; Keller, Lukas F; Losdat, Sylvain
2014-01-01
Ongoing evolution of polyandry, and consequent extra-pair reproduction in socially monogamous systems, is hypothesized to be facilitated by indirect selection stemming from cross-sex genetic covariances with components of male fitness. Specifically, polyandry is hypothesized to create positive genetic covariance with male paternity success due to inevitable assortative reproduction, driving ongoing coevolution. However, it remains unclear whether such covariances could or do emerge within complex polyandrous systems. First, we illustrate that genetic covariances between female extra-pair reproduction and male within-pair paternity success might be constrained in socially monogamous systems where female and male additive genetic effects can have opposing impacts on the paternity of jointly reared offspring. Second, we demonstrate nonzero additive genetic variance in female liability for extra-pair reproduction and male liability for within-pair paternity success, modeled as direct and associative genetic effects on offspring paternity, respectively, in free-living song sparrows (Melospiza melodia). The posterior mean additive genetic covariance between these liabilities was slightly positive, but the credible interval was wide and overlapped zero. Therefore, although substantial total additive genetic variance exists, the hypothesis that ongoing evolution of female extra-pair reproduction is facilitated by genetic covariance with male within-pair paternity success cannot yet be definitively supported or rejected either conceptually or empirically. PMID:24724612
Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore
2015-11-22
Given the pace at which human-induced environmental changes occur, a pressing challenge is to determine the speed with which selection can drive evolutionary change. A key determinant of adaptive response to multivariate phenotypic selection is the additive genetic variance-covariance matrix ( G: ). Yet knowledge of G: in a population experiencing new or altered selection is not sufficient to predict selection response because G: itself evolves in ways that are poorly understood. We experimentally evaluated changes in G: when closely related behavioural traits experience continuous directional selection. We applied the genetic covariance tensor approach to a large dataset (n = 17 328 individuals) from a replicated, 31-generation artificial selection experiment that bred mice for voluntary wheel running on days 5 and 6 of a 6-day test. Selection on this subset of G: induced proportional changes across the matrix for all 6 days of running behaviour within the first four generations. The changes in G: induced by selection resulted in a fourfold slower-than-predicted rate of response to selection. Thus, selection exacerbated constraints within G: and limited future adaptive response, a phenomenon that could have profound consequences for populations facing rapid environmental change. PMID:26582016
Characterizing the evolution of genetic variance using genetic covariance tensors.
Hine, Emma; Chenoweth, Stephen F; Rundle, Howard D; Blows, Mark W
2009-06-12
Determining how genetic variance changes under selection in natural populations has proved to be a very resilient problem in evolutionary genetics. In the same way that understanding the availability of genetic variance within populations requires the simultaneous consideration of genetic variance in sets of functionally related traits, determining how genetic variance changes under selection in natural populations will require ascertaining how genetic variance-covariance (G) matrices evolve. Here, we develop a geometric framework using higher-order tensors, which enables the empirical characterization of how G matrices have diverged among populations. We then show how divergence among populations in genetic covariance structure can then be associated with divergence in selection acting on those traits using key equations from evolutionary theory. Using estimates of G matrices of eight male sexually selected traits from nine geographical populations of Drosophila serrata, we show that much of the divergence in genetic variance occurred in a single trait combination, a conclusion that could not have been reached by examining variation among the individual elements of the nine G matrices. Divergence in G was primarily in the direction of the major axes of genetic variance within populations, suggesting that genetic drift may be a major cause of divergence in genetic variance among these populations. PMID:19414471
How much do genetic covariances alter the rate of adaptation?
Agrawal, Aneil F.; Stinchcombe, John R.
2008-01-01
Genetically correlated traits do not evolve independently, and the covariances between traits affect the rate at which a population adapts to a specified selection regime. To measure the impact of genetic covariances on the rate of adaptation, we compare the rate fitness increases given the observed G matrix to the expected rate if all the covariances in the G matrix are set to zero. Using data from the literature, we estimate the effect of genetic covariances in real populations. We find no net tendency for covariances to constrain the rate of adaptation, though the quality and heterogeneity of the data limit the certainty of this result. There are some examples in which covariances strongly constrain the rate of adaptation but these are balanced by counter examples in which covariances facilitate the rate of adaptation; in many cases, covariances have little or no effect. We also discuss how our metric can be used to identify traits or suites of traits whose genetic covariances to other traits have a particularly large impact on the rate of adaptation. PMID:19129097
Reid, J M; Arcese, P; Losdat, S
2014-01-01
The evolutionary trajectories of reproductive systems, including both male and female multiple mating and hence polygyny and polyandry, are expected to depend on the additive genetic variances and covariances in and among components of male reproductive success achieved through different reproductive tactics. However, genetic covariances among key components of male reproductive success have not been estimated in wild populations. We used comprehensive paternity data from socially monogamous but genetically polygynandrous song sparrows (Melospiza melodia) to estimate additive genetic variance and covariance in the total number of offspring a male sired per year outside his social pairings (i.e. his total extra-pair reproductive success achieved through multiple mating) and his liability to sire offspring produced by his socially paired female (i.e. his success in defending within-pair paternity). Both components of male fitness showed nonzero additive genetic variance, and the estimated genetic covariance was positive, implying that males with high additive genetic value for extra-pair reproduction also have high additive genetic propensity to sire their socially paired female's offspring. There was consequently no evidence of a genetic or phenotypic trade-off between male within-pair paternity success and extra-pair reproductive success. Such positive genetic covariance might be expected to facilitate ongoing evolution of polygyny and could also shape the ongoing evolution of polyandry through indirect selection. PMID:25186454
Páez, David James; Bernatchez, Louis; Dodson, Julian J.
2011-01-01
Alternative reproductive tactics are ubiquitous in many species. Tactic expression often depends on whether an individual's condition surpasses thresholds that are responsible for activating particular developmental pathways. Two central goals in understanding the evolution of reproductive tactics are quantifying the extent to which thresholds are explained by additive genetic effects, and describing their covariation with condition-related traits. We monitored the development of early sexual maturation that leads to the sneaker reproductive tactic in Atlantic salmon (Salmo salar L.). We found evidence for additive genetic variance in the timing of sexual maturity (which is a measure of the surpassing of threshold values) and body-size traits. This suggests that selection can affect the patterns of sexual development by changing the timing of this event and/or body size. Significant levels of covariation between these traits also occurred, implying a potential for correlated responses to selection. Closer examination of genetic covariances suggests that the detected genetic variation is distributed along at least five directions of phenotypic variation. Our results show that the potential for evolution of the life-history traits constituting this reproductive phenotype is greatly influenced by their patterns of genetic covariance. PMID:21177685
Natural variation and genetic covariance in adult hippocampal neurogenesis
Kempermann, Gerd; Chesler, Elissa J; Lu, Lu; Williams, Robert; Gage, Fred
2006-01-01
Adult hippocampal neurogenesis is highly variable and heritable among laboratory strains of mice. Adult neurogenesis is also remarkably plastic and can be modulated by environment and activity. Here, we provide a systematic quantitative analysis of adult hippocampal neurogenesis in two large genetic reference panels of recombinant inbred strains (BXD and AXB?BXA, n ? 52 strains). We combined data on variation in neurogenesis with a new transcriptome database to extract a set of 190 genes with expression patterns that are also highly variable and that covary with rates of (i) cell proliferation, (ii) cell survival, or the numbers of surviving (iii) new neurons, and (iv) astrocytes. Expression of a subset of these neurogenesis-associated transcripts was controlled in cis across the BXD set. These self-modulating genes are particularly interesting candidates to control neurogenesis. Among these were musashi (Msi1h) and prominin1?CD133 (Prom1), both of which are linked to stem-cell maintenance and division. Twelve neurogenesis-associated transcripts had significant cis-acting quantitative trait loci, and, of these, six had plausible biological association with adult neurogenesis (Prom1, Ssbp2, Kcnq2, Ndufs2, Camk4, and Kcnj9). Only one cis- cting candidate was linked to both neurogenesis and gliogenesis, Rapgef6, a downstream target of ras signaling. The use of genetic reference panels coupled with phenotyping and global transcriptome profiling thus allowed insight into the complexity of the genetic control of adult neurogenesis.
Hether, Tyler D; Hohenlohe, Paul A
2014-04-01
Systems biology is accumulating a wealth of understanding about the structure of genetic regulatory networks, leading to a more complete picture of the complex genotype-phenotype relationship. However, models of multivariate phenotypic evolution based on quantitative genetics have largely not incorporated a network-based view of genetic variation. Here we model a set of two-node, two-phenotype genetic network motifs, covering a full range of regulatory interactions. We find that network interactions result in different patterns of mutational (co)variance at the phenotypic level (the M-matrix), not only across network motifs but also across phenotypic space within single motifs. This effect is due almost entirely to mutational input of additive genetic (co)variance. Variation in M has the effect of stretching and bending phenotypic space with respect to evolvability, analogous to the curvature of space-time under general relativity, and similar mathematical tools may apply in each case. We explored the consequences of curvature in mutational variation by simulating adaptation under divergent selection with gene flow. Both standing genetic variation (the G-matrix) and rate of adaptation are constrained by M, so that G and adaptive trajectories are curved across phenotypic space. Under weak selection the phenotypic mean at migration-selection balance also depends on M. PMID:24219635
Mining associations between genetic markers, phenotypes, and covariates.
Sevon, P; Ollikainen, V; Onkamo, P; Toivonen, H T; Mannila, H; Kere, J
2001-01-01
We used Haplotype Pattern Mining, HPM [Toivonen et al., Am J Hum Genet 67:133-45, 2000], for gene localization in Genetic Analysis Workshop (GAW) 12 isolate data. In HPM, association is analyzed by searching all trait-associated haplotype patterns. Data mining algorithms are utilized to make the search efficient. The strength of the haplotype-trait associations is measured by a linear model, into which a pre-seelected set of covariates is incorporated. Marker-wise patterns of association are used for predicting the disease gene location. Genome-wide scans of susceptibility genes for affection status as well as for the quantitative traits (Q1-Q5) were performed. First analyses were made with small sample sizes, 63-94 trios per trait, which is compared with a pilot study of a larger complex disease-mapping project. Subsequently, the analysis was repeated with approximately 600 cases and 600 controls per trait to give higher power to the analyses. With small sample sizes, only the susceptibility genes having the strongest effects on the traits could be localized. The larger sample size gave very good results: all susceptibility genes, except one, could be correctly localized. First experiments on candidate genes suggested that HPM is applicable even to fine mapping of mutations in DNA sequence. PMID:11793743
Bezdjian, Serena; Tuvblad, Catherine; Raine, Adrian; Baker, Laura A
2011-01-01
The present study investigated the genetic and environmental covariance between psychopathic personality traits with reactive and proactive aggression in 9- to 10-year-old twins (N = 1,219). Psychopathic personality traits were assessed with the Child Psychopathy Scale (D. R. Lynam, 1997), while aggressive behaviors were assessed using the Reactive Proactive Questionnaire (A. Raine et al., 2006). Significant common genetic influences were found to be shared by psychopathic personality traits and aggressive behaviors using both caregiver (mainly mother) and child self-reports. Significant genetic and nonshared environmental influences specific to psychopathic personality traits and reactive and proactive aggression were also found, suggesting etiological independence among these phenotypes. Additionally, the genetic relation between psychopathic personality traits and aggression was significantly stronger for proactive than reactive aggression when using child self-reports. PMID:21557742
The causes of variation in the presence of genetic covariance between sexual traits and preferences.
Fowler-Finn, Kasey D; Rodríguez, Rafael L
2016-05-01
Mating traits and mate preferences often show patterns of tight correspondence across populations and species. These patterns of apparent coevolution may result from a genetic association between traits and preferences (i.e. trait-preference genetic covariance). We review the literature on trait-preference covariance to determine its prevalence and potential biological relevance. Of the 43 studies we identified, a surprising 63% detected covariance. We test multiple hypotheses for factors that may influence the likelihood of detecting this covariance. The main predictor was the presence of genetic variation in mate preferences, which is one of the three main conditions required for the establishment of covariance. In fact, 89% of the nine studies where heritability of preference was high detected covariance. Variables pertaining to the experimental methods and type of traits involved in different studies did not greatly influence the detection of trait-preference covariance. Trait-preference genetic covariance appears to be widespread and therefore represents an important and currently underappreciated factor in the coevolution of traits and preferences. PMID:25808899
An alternative covariance estimator to investigate genetic heterogeneity in populations
Technology Transfer Automated Retrieval System (TEKTRAN)
Genomic predictions and GWAS have used mixed models for identification of associations and trait predictions. In both cases, the covariance between individuals for performance is estimated using molecular markers. Mixed model properties indicate that the use of the data for prediction is optimal if ...
Meyer, Karin
2001-01-01
A random regression model for the analysis of "repeated" records in animal breeding is described which combines a random regression approach for additive genetic and other random effects with the assumption of a parametric correlation structure for within animal covariances. Both stationary and non-stationary correlation models involving a small number of parameters are considered. Heterogeneity in within animal variances is modelled through polynomial variance functions. Estimation of parameters describing the dispersion structure of such model by restricted maximum likelihood via an "average information" algorithm is outlined. An application to mature weight records of beef cow is given, and results are contrasted to those from analyses fitting sets of random regression coefficients for permanent environmental effects. PMID:11742630
Houle, D; Meyer, K
2015-08-01
We explore the estimation of uncertainty in evolutionary parameters using a recently devised approach for resampling entire additive genetic variance-covariance matrices (G). Large-sample theory shows that maximum-likelihood estimates (including restricted maximum likelihood, REML) asymptotically have a multivariate normal distribution, with covariance matrix derived from the inverse of the information matrix, and mean equal to the estimated G. This suggests that sampling estimates of G from this distribution can be used to assess the variability of estimates of G, and of functions of G. We refer to this as the REML-MVN method. This has been implemented in the mixed-model program WOMBAT. Estimates of sampling variances from REML-MVN were compared to those from the parametric bootstrap and from a Bayesian Markov chain Monte Carlo (MCMC) approach (implemented in the R package MCMCglmm). We apply each approach to evolvability statistics previously estimated for a large, 20-dimensional data set for Drosophila wings. REML-MVN and MCMC sampling variances are close to those estimated with the parametric bootstrap. Both slightly underestimate the error in the best-estimated aspects of the G matrix. REML analysis supports the previous conclusion that the G matrix for this population is full rank. REML-MVN is computationally very efficient, making it an attractive alternative to both data resampling and MCMC approaches to assessing confidence in parameters of evolutionary interest. PMID:26079756
Moore, Mollie N.; Shirtcliff, Elizabeth A.; Lemery-Chalfant, Kathryn; Goldsmith, H. Hill
2015-01-01
Although several studies have shown that pubertal tempo and timing are shaped by genetic and environmental factors, few studies consider to what extent endocrine triggers of puberty are shaped by genetic and environmental factors. Doing so moves the field from examining correlated developmentally-sensitive biomarkers toward understanding what drives those associations. Two puberty related hormones, dehydroepiandrosterone and testosterone, were assayed from salivary samples in 118 MZ (62 % female), 111 same sex DZ (46 % female) and 103 opposite-sex DZ twin pairs, aged 12–16 years (M = 13.1, SD = 1.3). Pubertal status was assessed with a composite of mother- and self-reports. We used biometric models to estimate the genetic and environmental influences on the variance and covariance in testosterone and DHEA, with and without controlling for their association with puberty, and to test for sex differences. In males, the variance in testosterone and pubertal status was due to shared and non-shared environmental factors; variation in DHEA was due to genetic and non-shared environmental factors. In females, variance in testosterone was due to genetic and non-shared environmental factors; genetic, shared, and non-shared environmental factors contributed equally to variation in DHEA. In males, the testosterone-DHEA covariance was primarily due to shared environmental factors that overlapped with puberty as well as shared and non-shared environmental covariation specific to testosterone and DHEA. In females, the testosterone-DHEA covariance was due to genetic factors overlapping with pubertal status, and shared and non-shared environmental covariation specific to testosterone and DHEA. PMID:25633628
Evolutionary response when selection and genetic variation covary across environments.
Wood, Corlett W; Brodie, Edmund D
2016-10-01
Although models of evolution usually assume that the strength of selection on a trait and the expression of genetic variation in that trait are independent, whenever the same ecological factor impacts both parameters, a correlation between the two may arise that accelerates trait evolution in some environments and slows it in others. Here, we address the evolutionary consequences and ecological causes of a correlation between selection and expressed genetic variation. Using a simple analytical model, we show that the correlation has a modest effect on the mean evolutionary response and a large effect on its variance, increasing among-population or among-generation variation in the response when positive, and diminishing variation when negative. We performed a literature review to identify the ecological factors that influence selection and expressed genetic variation across traits. We found that some factors - temperature and competition - are unlikely to generate the correlation because they affected one parameter more than the other, and identified others - most notably, environmental novelty - that merit further investigation because little is known about their impact on one of the two parameters. We argue that the correlation between selection and genetic variation deserves attention alongside other factors that promote or constrain evolution in heterogeneous landscapes. PMID:27531600
Genetic diversity and species diversity of stream fishes covary across a land-use gradient
Blum, M.J.; Bagley, M.J.; Walters, D.M.; Jackson, S.A.; Daniel, F.B.; Chaloud, D.J.; Cade, B.S.
2012-01-01
Genetic diversity and species diversity are expected to covary according to area and isolation, but may not always covary with environmental heterogeneity. In this study, we examined how patterns of genetic and species diversity in stream fishes correspond to local and regional environmental conditions. To do so, we compared population size, genetic diversity and divergence in central stonerollers (Campostoma anomalum) to measures of species diversity and turnover in stream fish assemblages among similarly sized watersheds across an agriculture-forest land-use gradient in the Little Miami River basin (Ohio, USA). Significant correlations were found in many, but not all, pair-wise comparisons. Allelic richness and species richness were strongly correlated, for example, but diversity measures based on allele frequencies and assemblage structure were not. In-stream conditions related to agricultural land use were identified as significant predictors of genetic diversity and species diversity. Comparisons to population size indicate, however, that genetic diversity and species diversity are not necessarily independent and that variation also corresponds to watershed location and glaciation history in the drainage basin. Our findings demonstrate that genetic diversity and species diversity can covary in stream fish assemblages, and illustrate the potential importance of scaling observations to capture responses to hierarchical environmental variation. More comparisons according to life history variation could further improve understanding of conditions that give rise to parallel variation in genetic diversity and species diversity, which in turn could improve diagnosis of anthropogenic influences on aquatic ecosystems. ?? 2011 Springer-Verlag.
ERIC Educational Resources Information Center
Bezdjian, Serena; Tuvblad, Catherine; Raine, Adrian; Baker, Laura A.
2011-01-01
The present study investigated the genetic and environmental covariance between psychopathic personality traits with reactive and proactive aggression in 9- to 10-year-old twins (N = 1,219). Psychopathic personality traits were assessed with the Child Psychopathy Scale (D. R. Lynam, 1997), while aggressive behaviors were assessed using the…
The evolutionary stability of cross-sex, cross-trait genetic covariances.
Gosden, Thomas P; Chenoweth, Stephen F
2014-06-01
Although knowledge of the selective agents behind the evolution of sexual dimorphism has advanced considerably in recent years, we still lack a clear understanding of the evolutionary durability of cross-sex genetic covariances that often constrain its evolution. We tested the relative stability of cross-sex genetic covariances for a suite of homologous contact pheromones of the fruit fly Drosophila serrata, along a latitudinal gradient where these traits have diverged in mean. Using a Bayesian framework, which allowed us to account for uncertainty in all parameter estimates, we compared divergence in the total amount and orientation of genetic variance across populations, finding divergence in orientation but not total variance. We then statistically compared orientation divergence of within-sex (G) to cross-sex (B) covariance matrices. In line with a previous theoretical prediction, we find that the cross-sex covariance matrix, B, is more variable than either within-sex G matrix. Decomposition of B matrices into their symmetrical and nonsymmetrical components revealed that instability is linked to the degree of asymmetry. We also find that the degree of asymmetry correlates with latitude suggesting a role for spatially varying natural selection in shaping genetic constraints on the evolution of sexual dimorphism. PMID:24620712
Sarmento, J L R; Torres, R A; Sousa, W H; Lôbo, R N B; Albuquerque, L G; Lopes, P S; Santos, N P S; Bignard, A B
2016-01-01
Polynomial functions of different orders were used to model random effects associated with weight of Santa Ines sheep from birth to 196 days. Fixed effects included in the models were contemporary groups, age of ewe at lambing, and fourth-order Legendre polynomials for age to represent the average growth curve. In the random part, functions of different orders were included to model variances associated with direct additive and maternal genetic effects and with permanent environmental effects of the animal and mother. Residual variance was fitted by a sixth-order ordinary polynomial for age. The higher the order of the functions, the better the model fit the data. According to the Akaike information criterion and likelihood ratio test, a continuous function of order, five, five, seven, and three for direct additive genetic, maternal genetic, animal permanent environmental, and maternal permanent environmental effects (k = 5573), respectively, was sufficient to model changes in (co)variances with age. However, a more parsimonious model of order three, three, five, and three (k = 3353) was suggested based on Schwarz's Bayesian information criterion for the same effects. Since it was a more flexible model, model k = 5573 provided inconsistent genetic parameter estimates when compared to the biologically expected result. Predicted breeding values obtained with models k = 3353 and k = 5573 differed, especially at young ages. Model k = 3353 adequately fit changes in variances and covariances with time, and may be used to describe changes in variances with age in the Santa Ines sheep studied. PMID:27323203
Genetic variances and covariances of aerobic metabolic rates in laboratory mice
Wone, Bernard; Sears, Michael W.; Labocha, Marta K.; Donovan, Edward R.; Hayes, Jack P.
2009-01-01
The genetic variances and covariances of traits must be known to predict how they may respond to selection and how covariances among them might affect their evolutionary trajectories. We used the animal model to estimate the genetic variances and covariances of basal metabolic rate (BMR) and maximal metabolic rate (MMR) in a genetically heterogeneous stock of laboratory mice. Narrow-sense heritability (h2) was approximately 0.38 ± 0.08 for body mass, 0.26 ± 0.08 for whole-animal BMR, 0.24 ± 0.07 for whole-animal MMR, 0.19 ± 0.07 for mass-independent BMR, and 0.16 ± 0.06 for mass-independent MMR. All h2 estimates were significantly different from zero. The phenotypic correlation of whole animal BMR and MMR was 0.56 ± 0.02, and the corresponding genetic correlation was 0.79 ± 0.12. The phenotypic correlation of mass-independent BMR and MMR was 0.13 ± 0.03, and the corresponding genetic correlation was 0.72 ± 0.03. The genetic correlations of metabolic rates were significantly different from zero, but not significantly different from one. A key assumption of the aerobic capacity model for the evolution of endothermy is that BMR and MMR are linked. The estimated genetic correlation between BMR and MMR is consistent with that assumption, but the genetic correlation is not so high as to preclude independent evolution of BMR and MMR. PMID:19656796
Vitezica, Zulma G.; Varona, Luis; Legarra, Andres
2013-01-01
Genomic evaluation models can fit additive and dominant SNP effects. Under quantitative genetics theory, additive or “breeding” values of individuals are generated by substitution effects, which involve both “biological” additive and dominant effects of the markers. Dominance deviations include only a portion of the biological dominant effects of the markers. Additive variance includes variation due to the additive and dominant effects of the markers. We describe a matrix of dominant genomic relationships across individuals, D, which is similar to the G matrix used in genomic best linear unbiased prediction. This matrix can be used in a mixed-model context for genomic evaluations or to estimate dominant and additive variances in the population. From the “genotypic” value of individuals, an alternative parameterization defines additive and dominance as the parts attributable to the additive and dominant effect of the markers. This approach underestimates the additive genetic variance and overestimates the dominance variance. Transforming the variances from one model into the other is trivial if the distribution of allelic frequencies is known. We illustrate these results with mouse data (four traits, 1884 mice, and 10,946 markers) and simulated data (2100 individuals and 10,000 markers). Variance components were estimated correctly in the model, considering breeding values and dominance deviations. For the model considering genotypic values, the inclusion of dominant effects biased the estimate of additive variance. Genomic models were more accurate for the estimation of variance components than their pedigree-based counterparts. PMID:24121775
Ingleby, F C; Innocenti, P; Rundle, H D; Morrow, E H
2014-08-01
Males and females share much of their genome, and as a result, intralocus sexual conflict is generated when selection on a shared trait differs between the sexes. This conflict can be partially or entirely resolved via the evolution of sex-specific genetic variation that allows each sex to approach, or possibly achieve, its optimum phenotype, thereby generating sexual dimorphism. However, shared genetic variation between the sexes can impose constraints on the independent expression of a shared trait in males and females, hindering the evolution of sexual dimorphism. Here, we examine genetic constraints on the evolution of sexual dimorphism in Drosophila melanogaster cuticular hydrocarbon (CHC) expression. We use the extended G matrix, which includes the between-sex genetic covariances that constitute the B matrix, to compare genetic constraints on two sets of CHC traits that differ in the extent of their sexual dimorphism. We find significant genetic constraints on the evolution of further dimorphism in the least dimorphic traits, but no such constraints for the most dimorphic traits. We also show that the genetic constraints on the least dimorphic CHCs are asymmetrical between the sexes. Our results suggest that there is evidence both for resolved and ongoing sexual conflict in D. melanogaster CHC profiles. PMID:24893565
Determining the Effective Dimensionality of the Genetic Variance–Covariance Matrix
Hine, Emma; Blows, Mark W.
2006-01-01
Determining the dimensionality of G provides an important perspective on the genetic basis of a multivariate suite of traits. Since the introduction of Fisher's geometric model, the number of genetically independent traits underlying a set of functionally related phenotypic traits has been recognized as an important factor influencing the response to selection. Here, we show how the effective dimensionality of G can be established, using a method for the determination of the dimensionality of the effect space from a multivariate general linear model introduced by Amemiya (1985). We compare this approach with two other available methods, factor-analytic modeling and bootstrapping, using a half-sib experiment that estimated G for eight cuticular hydrocarbons of Drosophila serrata. In our example, eight pheromone traits were shown to be adequately represented by only two underlying genetic dimensions by Amemiya's approach and factor-analytic modeling of the covariance structure at the sire level. In contrast, bootstrapping identified four dimensions with significant genetic variance. A simulation study indicated that while the performance of Amemiya's method was more sensitive to power constraints, it performed as well or better than factor-analytic modeling in correctly identifying the original genetic dimensions at moderate to high levels of heritability. The bootstrap approach consistently overestimated the number of dimensions in all cases and performed less well than Amemiya's method at subspace recovery. PMID:16547106
Luciano, Michelle; Wright, Margaret J; Geffen, Gina M; Geffen, Laurie B; Smith, Glen A; Martin, Nicholas G
2004-01-01
Information processing speed, as measured by elementary cognitive tasks, is correlated with higher order cognitive ability so that increased speed relates to improved cognitive performance. The question of whether the genetic variation in Inspection Time (IT) and Choice Reaction Time (CRT) is associated with IQ through a unitary factor was addressed in this multivariate genetic study of IT, CRT, and IQ subtest scores. The sample included 184 MZ and 206 DZ twin pairs with a mean age of 16.2 years (range 15-18 years). They were administered a visual (pi-figure) IT task, a two-choice RT task, five computerized subtests of the Multidimensional Aptitude Battery, and the digit symbol substitution subtest from the WAIS-R. The data supported a factor model comprising a general, three group (verbal ability, visuospatial ability, broad speediness), and specific genetic factor structure, a shared environmental factor influencing all tests but IT, plus unique environmental factors that were largely specific to individual measures. The general genetic factor displayed factor loadings ranging between 0.35 and 0.66 for the IQ subtests, with IT and CRT loadings of -0.47 and -0.24, respectively. Results indicate that a unitary factor is insufficient to describe the entire relationship between cognitive speed measures and all IQ subtests, with independent genetic effects explaining further covariation between processing speed (especially CRT) and Digit Symbol. PMID:14739695
Fu, C.Y.; Hetrick, D.M.
1982-01-01
Recent ratio data, with carefully evaluated covariances, were combined with eleven of the ENDF/B-V dosimetry cross sections using the generalized least-squares method. The purpose was to improve these evaluated cross sections and covariances, as well as to generate values for the cross-reaction covariances. The results represent improved cross sections as well as realistic and usable covariances. The latter are necessary for meaningful intergral-differential comparisons and for spectrum unfolding.
Lange, Benjamin; Kaufmann, Andrea Patricia; Ebert, Dieter
2015-11-01
Parasites often have a smaller geographic distribution than their hosts. Common garden infection trials can untangle the role that historical contingencies, ecological conditions and the genetic constitution of local host populations play in limiting parasite geographic range; however, infection trials usually overestimate the range of hosts in which a parasite could naturally persist. This study overcomes that problem by using multigeneration, long-term persistence experiments. We study the microsporidian parasite Hamiltosporidium tvaerminnensis in monoclonal populations of Daphnia magna from 43 widely spread sites. The parasite persisted well in hosts collected from its natural geographic range, but demonstrated long-term persistence in only a few host genotypes outside this range. Genetic distance between hosts from the parasite's origin site and newly tested host populations correlated negatively with parasite persistence. Furthermore, the parasite persisted only in host populations from habitats with a high likelihood of drying up in summer, although we excluded environmental variation in our experiments. Together, our results suggest that host genetic factors play the dominant role in explaining the limited geographic range of parasites and that these genetic differences covary with geographic distance and the habitat type the host is adapted to. PMID:26147623
Griswold, Cortland K
2015-12-21
Epistatic gene action occurs when mutations or alleles interact to produce a phenotype. Theoretically and empirically it is of interest to know whether gene interactions can facilitate the evolution of diversity. In this paper, we explore how epistatic gene action affects the additive genetic component or heritable component of multivariate trait variation, as well as how epistatic gene action affects the evolvability of multivariate traits. The analysis involves a sexually reproducing and recombining population. Our results indicate that under stabilizing selection conditions a population with a mixed additive and epistatic genetic architecture can have greater multivariate additive genetic variation and evolvability than a population with a purely additive genetic architecture. That greater multivariate additive genetic variation can occur with epistasis is in contrast to previous theory that indicated univariate additive genetic variation is decreased with epistasis under stabilizing selection conditions. In a multivariate setting, epistasis leads to less relative covariance among individuals in their genotypic, as well as their breeding values, which facilitates the maintenance of additive genetic variation and increases a population׳s evolvability. Our analysis involves linking the combinatorial nature of epistatic genetic effects to the ancestral graph structure of a population to provide insight into the consequences of epistasis on multivariate trait variation and evolution. PMID:26431770
Kong, Jing; Wang, Sijian; Wahba, Grace
2015-05-10
Variable selection is of increasing importance to address the difficulties of high dimensionality in many scientific areas. In this paper, we demonstrate a property for distance covariance, which is incorporated in a novel feature screening procedure together with the use of distance correlation. The approach makes no distributional assumptions for the variables and does not require the specification of a regression model and hence is especially attractive in variable selection given an enormous number of candidate attributes without much information about the true model with the response. The method is applied to two genetic risk problems, where issues including uncertainty of variable selection via cross validation, subgroup of hard-to-classify cases, and the application of a reject option are discussed. PMID:25640961
Del Monego, Maurici; Ribeiro, Paulo Justiniano; Ramos, Patrícia
2015-04-01
In this work, kriging with covariates is used to model and map the spatial distribution of salinity measurements gathered by an autonomous underwater vehicle in a sea outfall monitoring campaign aiming to distinguish the effluent plume from the receiving waters and characterize its spatial variability in the vicinity of the discharge. Four different geostatistical linear models for salinity were assumed, where the distance to diffuser, the west-east positioning, and the south-north positioning were used as covariates. Sample variograms were fitted by the Matèrn models using weighted least squares and maximum likelihood estimation methods as a way to detect eventual discrepancies. Typically, the maximum likelihood method estimated very low ranges which have limited the kriging process. So, at least for these data sets, weighted least squares showed to be the most appropriate estimation method for variogram fitting. The kriged maps show clearly the spatial variation of salinity, and it is possible to identify the effluent plume in the area studied. The results obtained show some guidelines for sewage monitoring if a geostatistical analysis of the data is in mind. It is important to treat properly the existence of anomalous values and to adopt a sampling strategy that includes transects parallel and perpendicular to the effluent dispersion. PMID:25345922
Explaining additional genetic variation in complex traits
Robinson, Matthew R.; Wray, Naomi R.; Visscher, Peter M.
2015-01-01
Genome-wide association studies (GWAS) have provided valuable insights into the genetic basis of complex traits, discovering >6000 variants associated with >500 quantitative traits and common complex diseases in humans. The associations identified so far represent only a fraction of those which influence phenotype, as there are likely to be very many variants across the entire frequency spectrum, each of which influences multiple traits, with only a small average contribution to the phenotypic variance. This presents a considerable challenge to further dissection of the remaining unexplained genetic variance within populations, which limits our ability to predict disease risk, identify new drug targets, improve and maintain food sources, and understand natural diversity. This challenge will be met within the current framework through larger sample size, better phenotyping including recording of non-genetic risk factors, focused study designs, and an integration of multiple sources of phenotypic and genetic information. The current evidence supports the application of quantitative genetic approaches, and we argue that one should retain simpler theories until simplicity can be traded for greater explanatory power. PMID:24629526
Wu, Yi-Ying; Yen, Ming-Fang; Yu, Cheng-Ping; Chen, Hsiu-Hsi
2014-02-01
Few studies have focused on the different roles risk factors play in the multistate temporal natural course of breast cancer. We proposed a three-state Markov regression model to predict the risk from free of breast cancer (FBC) to the preclinical screen-detectable phase (PCDP) and from the PCDP to the clinical phase (CP). We searched the initiators and promoters affecting onset and subsequent progression of breast tumor to build up a three-state temporal natural history model with state-dependent genetic and environmental covariates. This risk assessment model was applied to a 1 million Taiwanese women cohort. The proposed model was verified by external validation with another independent data set. We identified three kinds of initiators, including the BRCA gene, seven single nucleotides polymorphism, and breast density. ER, Ki-67, and HER-2 were found as promoters. Body mass index and age at first pregnancy both played a role. Among women carrying the BRCA gene, the 10-year predicted risk for the transition from FBC to CP was 25.83%, 20.31%, and 13.84% for the high-, intermediate-, and low-risk group, respectively. The corresponding figures were 1.55%, 1.22%, and 0.76% among noncarriers. The mean sojourn time of staying at the PCDP ranged from 0.82 years for the highest risk group to 6.21 years for the lowest group. The lack of statistical significance for external validation (x(4)2=5.30,p=0.26) revealed the adequacy of our proposed model. The three-state model with state-dependent covariates of initiators and promoters was proposed for achieving individually tailored screening and also for personalized clinical surveillance of early breast cancer. PMID:24111840
Donoghue, K A; Bird-Gardiner, T; Arthur, P F; Herd, R M; Hegarty, R F
2016-04-01
Ruminants contribute 80% of the global livestock greenhouse gas (GHG) emissions mainly through the production of methane, a byproduct of enteric microbial fermentation primarily in the rumen. Hence, reducing enteric methane production is essential in any GHG emissions reduction strategy in livestock. Data on 1,046 young bulls and heifers from 2 performance-recording research herds of Angus cattle were analyzed to provide genetic and phenotypic variance and covariance estimates for methane emissions and production traits and to examine the interrelationships among these traits. The cattle were fed a roughage diet at 1.2 times their estimated maintenance energy requirements and measured for methane production rate (MPR) in open circuit respiration chambers for 48 h. Traits studied included DMI during the methane measurement period, MPR, and methane yield (MY; MPR/DMI), with means of 6.1 kg/d (SD 1.3), 132 g/d (SD 25), and 22.0 g/kg (SD 2.3) DMI, respectively. Four forms of residual methane production (RMP), which is a measure of actual minus predicted MPR, were evaluated. For the first 3 forms, predicted MPR was calculated using published equations. For the fourth (RMP), predicted MPR was obtained by regression of MPR on DMI. Growth and body composition traits evaluated were birth weight (BWT), weaning weight (WWT), yearling weight (YWT), final weight (FWT), and ultrasound measures of eye muscle area, rump fat depth, rib fat depth, and intramuscular fat. Heritability estimates were moderate for MPR (0.27 [SE 0.07]), MY (0.22 [SE 0.06]), and the RMP traits (0.19 [SE 0.06] for each), indicating that genetic improvement to reduce methane emissions is possible. The RMP traits and MY were strongly genetically correlated with each other (0.99 ± 0.01). The genetic correlation of MPR with MY as well as with the RMP traits was moderate (0.32 to 0.63). The genetic correlation between MPR and the growth traits (except BWT) was strong (0.79 to 0.86). These results indicate that
Favaro, Angela; Tenconi, Elena; Bosello, Romina; Degortes, Daniela; Santonastaso, Paolo
2011-09-01
Although perinatal complications are hypothesized to be risk factors for the development of anorexia nervosa (AN), no study to date explored this issue using a discordant sibling design. This type of design allows to explore whether the risk for obstetric complications is itself a consequence of the genetic vulnerability for AN (covariation model) or whether obstetric complications increase the risk of AN independently of (additive model), or in interaction with (interaction model), the disorder's genetic liability. The presence of perinatal complications was assessed through review of the obstetric records of 60 AN subjects, 60 unaffected sisters, and 70 healthy subjects. Unaffected sisters and healthy controls were compared in relation to perinatal characteristics and complications. There was no evidence for an elevated rate of complications in unaffected siblings of AN patients. Mothers with a positive psychiatric history tended to have more perinatal complications. Perinatal complications seem to be independent risk factors that may interact with, but are not caused by, familial risk factors for AN. In terms of prevention, a particular attention should be paid to mothers with a lifetime history of psychiatric disorders. PMID:21193995
Unnatural reactive amino acid genetic code additions
Deiters, Alexander; Cropp, T. Ashton; Chin, Jason W.; Anderson, J. Christopher; Schultz, Peter G.
2011-08-09
This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNAsyn-thetases, pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.
Unnatural reactive amino acid genetic code additions
Deiters, Alexander; Cropp, Ashton T; Chin, Jason W; Anderson, Christopher J; Schultz, Peter G
2013-05-21
This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNA synthetases, pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.
Unnatural reactive amino acid genetic code additions
Deiters, Alexander; Cropp, T. Ashton; Chin, Jason W.; Anderson, J. Christopher; Schultz, Peter G.
2014-08-26
This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNA synthetases, orthogonal pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.
Unnatural reactive amino acid genetic code additions
Deiters, Alexander; Cropp, T. Ashton; Chin, Jason W.; Anderson, J. Christopher; Schultz, Peter G.
2011-02-15
This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNA synthetases, orthogonal pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.
Brock, Marcus T.; Dechaine, Jennifer M.; Iniguez-Luy, Federico L.; Maloof, Julin N.; Stinchcombe, John R.; Weinig, Cynthia
2010-01-01
Genetic correlations are expected to be high among functionally related traits and lower between groups of traits with distinct functions (e.g., reproductive vs. resource-acquisition traits). Here, we explore the quantitative-genetic and QTL architecture of floral organ sizes, vegetative traits, and life history in a set of Brassica rapa recombinant inbred lines within and across field and greenhouse environments. Floral organ lengths were strongly positively correlated within both environments, and analysis of standardized G-matrices indicates that the structure of genetic correlations is ∼80% conserved across environments. Consistent with these correlations, we detected a total of 19 and 21 additive-effect floral QTL in the field and the greenhouse, respectively, and individual QTL typically affected multiple organ types. Interestingly, QTL × QTL epistasis also appeared to contribute to observed genetic correlations; i.e., interactions between two QTL had similar effects on filament length and two estimates of petal size. Although floral and nonfloral traits are hypothesized to be genetically decoupled, correlations between floral organ size and both vegetative and life-history traits were highly significant in the greenhouse; G-matrices of floral and vegetative traits as well as floral and life-history traits differed across environments. Correspondingly, many QTL (45% of those mapped in the greenhouse) showed environmental interactions, including approximately even numbers of floral and nonfloral QTL. Most instances of QTL × QTL epistasis for floral traits were environment dependent. PMID:20837996
Nietlisbach, Pirmin; Hadfield, Jarrod D
2015-07-01
Whenever allele frequencies are unequal, nonadditive gene action contributes to additive genetic variance and therefore the resemblance between parents and offspring. The reason for this has not been easy to understand. Here, we present a new single-locus decomposition of additive genetic variance that may give greater intuition about this important result. We show that the contribution of dominant gene action to parent-offspring resemblance only depends on the degree to which the heterozygosity of parents and offspring covary. Thus, dominant gene action only contributes to additive genetic variance when heterozygosity is heritable. Under most circumstances this is the case because individuals with rare alleles are more likely to be heterozygous, and because they pass rare alleles to their offspring they also tend to have heterozygous offspring. When segregating alleles are at equal frequency there are no rare alleles, the heterozygosities of parents and offspring are uncorrelated and dominant gene action does not contribute to additive genetic variance. PMID:26100570
Genetic Influence on the Variance in Coincidence Timing and Its Covariance with IQ: A Twin Study.
ERIC Educational Resources Information Center
Wright, Margaret J.; Smith, Glen A.; Geffen, Gina M.; Geffen, Laurie B.; Martin, Nicholas G.
2000-01-01
Studied whether genetic variability explained some of the variance in coincidence timing and whether common genetic factors accounted for the association with intellectual functioning using 55 pairs of 16-year-old twins. Results suggest that the genetic influence operating on coincidence timing skills was of similar magnitude to that of response…
Huchard, E; Charmantier, A; English, S; Bateman, A; Nielsen, J F; Clutton-Brock, T
2014-09-01
Individual variation in growth is high in cooperative breeders and may reflect plastic divergence in developmental trajectories leading to breeding vs. helping phenotypes. However, the relative importance of additive genetic variance and developmental plasticity in shaping growth trajectories is largely unknown in cooperative vertebrates. This study exploits weekly sequences of body mass from birth to adulthood to investigate sources of variance in, and covariance between, early and later growth in wild meerkats (Suricata suricatta), a cooperative mongoose. Our results indicate that (i) the correlation between early growth (prior to nutritional independence) and adult mass is positive but weak, and there are frequent changes (compensatory growth) in post-independence growth trajectories; (ii) among parameters describing growth trajectories, those describing growth rate (prior to and at nutritional independence) show undetectable heritability while associated size parameters (mass at nutritional independence and asymptotic mass) are moderately heritable (0.09 ≤ h(2) < 0.3); and (iii) additive genetic effects, rather than early environmental effects, mediate the covariance between early growth and adult mass. These results reveal that meerkat growth trajectories remain plastic throughout development, rather than showing early and irreversible divergence, and that the weak effects of early growth on adult mass, an important determinant of breeding success, are partly genetic. In contrast to most cooperative invertebrates, the acquisition of breeding status is often determined after sexual maturity and strongly impacted by chance in many cooperative vertebrates, who may therefore retain the ability to adjust their morphology to environmental changes and social opportunities arising throughout their development, rather than specializing early. PMID:24962704
Wang, Pan; Gao, Yu; Isen, Joshua; Tuvblad, Catherine; Raine, Adrian; Baker, Laura A
2015-11-01
The genetic architecture of the association between psychopathic traits and reduced skin conductance responses (SCRs) is poorly understood. By using 752 twins aged 9-10 years, this study investigated the heritability of two SCR measures (anticipatory SCRs to impending aversive stimuli and unconditioned SCRs to the aversive stimuli themselves) in a countdown task. The study also investigated the genetic and environmental sources of the covariance between these SCR measures and two psychopathic personality traits: impulsive/disinhibited (reflecting impulsive-antisocial tendencies) and manipulative/deceitful (reflecting the affective-interpersonal features). For anticipatory SCRs, 27%, 14%, and 59% of the variation was due to genetic, shared environmental, and nonshared environmental effects, respectively, while the percentages for unconditioned SCRs were 44%, 2%, and 54%. The manipulative/deceitful (not impulsive/disinhibited) traits were negatively associated with both anticipatory SCRs (r = -.14, p < .05) and unconditioned SCRs (r = -.17, p < .05) in males only, with the former association significantly accounted for by genetic influences (r g = -.72). Reduced anticipatory SCRs represent a candidate endophenotype for the affective-interpersonal facets of psychopathic traits in males. PMID:26439076
WANG, PAN; GAO, YU; ISEN, JOSHUA; TUVBLAD, CATHERINE; RAINE, ADRIAN; BAKER, LAURA A.
2015-01-01
The genetic architecture of the association between psychopathic traits and reduced skin conductance responses (SCRs) is poorly understood. By using 752 twins aged 9–10 years, this study investigated the heritability of two SCR measures (anticipatory SCRs to impending aversive stimuli and unconditioned SCRs to the aversive stimuli themselves) in a countdown task. The study also investigated the genetic and environmental sources of the covariance between these SCR measures and two psychopathic personality traits: impulsive/disinhibited (reflecting impulsive–antisocial tendencies) and manipulative/deceitful (reflecting the affective–interpersonal features). For anticipatory SCRs, 27%, 14%, and 59% of the variation was due to genetic, shared environmental, and nonshared environmental effects, respectively, while the percentages for unconditioned SCRs were 44%, 2%, and 54%. The manipulative/deceitful (not impulsive/disinhibited) traits were negatively associated with both anticipatory SCRs (r = −.14, p < .05) and unconditioned SCRs (r = −.17, p < .05) in males only, with the former association significantly accounted for by genetic influences (rg = −.72). Reduced anticipatory SCRs represent a candidate endophenotype for the affective–interpersonal facets of psychopathic traits in males. PMID:26439076
ERIC Educational Resources Information Center
McAdams, Tom; Rowe, Richard; Rijsdijk, Fruhling; Maughan, Barbara; Eley, Thalia C.
2012-01-01
Multivariate genetic studies have revealed genetic correlations between antisocial behavior (ASB) and substance use (SU). However, ASB is heterogeneous, and it remains unclear whether all forms are similarly related to SU. The present study examines links between cannabis use, alcohol consumption, and aggressive and delinquent forms of ASB using a…
Bacchetti, Peter; Quale, Christopher
2002-06-01
We describe a method for extending smooth nonparametric modeling methods to time-to-event data where the event may be known only to lie within a window of time. Maximum penalized likelihood is used to fit a discrete proportional hazards model that also models the baseline hazard, and left-truncation and time-varying covariates are accommodated. The implementation follows generalized additive modeling conventions, allowing both parametric and smooth terms and specifying the amount of smoothness in terms of the effective degrees of freedom. We illustrate the method on a well-known interval-censored data set on time of human immunodeficiency virus infection in a multicenter study of hemophiliacs. The ability to examine time-varying covariates, not available with previous methods, allows detection and modeling of nonproportional hazards and use of a time-varying covariate that fits the data better and is more plausible than a fixed alternative. PMID:12071419
Converse, Sarah J.; Royle, J. Andrew; Urbanek, Richard P.
2012-01-01
Inbreeding depression is frequently a concern of managers interested in restoring endangered species. Decisions to reduce the potential for inbreeding depression by balancing genotypic contributions to reintroduced populations may exact a cost on long-term demographic performance of the population if those decisions result in reduced numbers of animals released and/or restriction of particularly successful genotypes (i.e., heritable traits of particular family lines). As part of an effort to restore a migratory flock of Whooping Cranes (Grus americana) to eastern North America using the offspring of captive breeders, we obtained a unique dataset which includes post-release mark-recapture data, as well as the pedigree of each released individual. We developed a Bayesian formulation of a multi-state model to analyze radio-telemetry, band-resight, and dead recovery data on reintroduced individuals, in order to track survival and breeding state transitions. We used studbook-based individual covariates to examine the comparative evidence for and degree of effects of inbreeding, genotype, and genotype quality on post-release survival of reintroduced individuals. We demonstrate implementation of the Bayesian multi-state model, which allows for the integration of imperfect detection, multiple data types, random effects, and individual- and time-dependent covariates. Our results provide only weak evidence for an effect of the quality of an individual's genotype in captivity on post-release survival as well as for an effect of inbreeding on post-release survival. We plan to integrate our results into a decision-analytic modeling framework that can explicitly examine tradeoffs between the effects of inbreeding and the effects of genotype and demographic stochasticity on population establishment.
Elzo, M A; West, R L; Johnson, D D; Wakeman, D L
1998-07-01
Estimates of covariances and sire expected progeny differences of additive and nonadditive genetic effects for six carcass traits were obtained using records from 486 straightbred and crossbred steers from 121 sires born between 1989 and 1995 in the Angus-Brahman multibreed herd of the University of Florida. Steers were slaughtered at a similar carcass composition end point. Covariances were estimated by REML procedures, using a generalized expectation-maximization algorithm applied to multibreed populations. Straightbred and crossbred estimates of heritabilities and additive genetic correlations were within ranges found in the literature for steers slaughtered on an age- or weight-constant basis for hot carcass weight, longissimus muscle area, and shear force but equal to or less than the lower bound of these ranges for fat-related traits. Maximum values of interactibilities (i.e., ratios of nonadditive variances to phenotypic variances in the F1) and nonadditive genetic correlations were smaller than heritabilities and additive genetic correlations in straightbreds and crossbred groups. Sire additive and total direct genetic predictions for longissimus muscle area, marbling, and shear force tended to decrease with the fraction of Brahman alleles, whereas those for hot carcass weight and fat thickness over the longissimus were higher, and those for kidney fat were lower in straightbreds and F1 than in other crossbred groups. Nonadditive genetic predictions were similar across sire groups of all Angus and Brahman fractions. These results suggest that slaughtering steers on a similar carcass composition basis reduces variability of fat-related traits while retaining variability for non-fat-related traits comparable to slaughtering steers on a similar age or weight basis. Selection for carcass traits within desirable (narrow) ranges and slaughter of steers at similar compositional end point seems to be a good combination to help produce meat products of consistent
Genetic (Co)Variation for Life Span in Rhabditid Nematodes: Role of Mutation, Selection, and History
Upadhyay, Ambuj; Salomon, Matthew P.; Grigaltchik, Veronica; Baer, Charles F.
2009-01-01
The evolutionary mechanisms maintaining genetic variation in life span, particularly post-reproductive life span, are poorly understood. We characterized the effects of spontaneous mutations on life span in the rhabditid nematodes Caenorhabditis elegans and C. briggsae and standing genetic variance for life span and correlation of life span with fitness in C. briggsae. Mutations decreased mean life span, a signature of directional selection. Mutational correlations between life span and fitness were consistently positive. The average selection coefficient against new mutations in C. briggsae was approximately 2% when homozygous. The pattern of phylogeographic variation in life span is inconsistent with global mutation–selection balance (MSB), but MSB appears to hold at the local level. Standing genetic correlations in C. briggsae reflect mutational correlations at a local scale but not at a broad phylogeographic level. At the local scale, results are broadly consistent with predictions of the “mutation accumulation” hypothesis for the evolution of aging. PMID:19671885
Ratterman, Nicholas L.; Rosenthal, Gil G.; Carney, Ginger E.; Jones, Adam G.
2013-01-01
How mating preferences evolve remains one of the major unsolved mysteries in evolutionary biology. One major impediment to the study of ornament-preference coevolution is that many aspects of the theoretical literature remain loosely connected to empirical data. Theoretical models typically streamline mating preferences by describing preference functions with a single parameter, a modeling convenience that may veil important aspects of preference evolution. Here, we use a high-throughput behavioral assay in Drosophila melanogaster to quantify attractiveness and multiple components of preferences in both males and females. Females varied genetically with respect to how they ranked males in terms of attractiveness as well as the extent to which they discriminated among different males. Conversely, males showed consistent preferences for females, suggesting that D. melanogaster males tend to rank different female phenotypes in the same order in terms of attractiveness. Moreover, we reveal a heretofore undocumented positive genetic correlation between male attractiveness and female choosiness, which is a measure of the variability in a female’s response to different male phenotypes. This genetic correlation sets the stage for female choosiness to evolve via a correlated response to selection on male traits and potentially adds a new dimension to the Fisherian sexual selection process. PMID:24212081
Efficient Improvement of Silage Additives by Using Genetic Algorithms
Davies, Zoe S.; Gilbert, Richard J.; Merry, Roger J.; Kell, Douglas B.; Theodorou, Michael K.; Griffith, Gareth W.
2000-01-01
The enormous variety of substances which may be added to forage in order to manipulate and improve the ensilage process presents an empirical, combinatorial optimization problem of great complexity. To investigate the utility of genetic algorithms for designing effective silage additive combinations, a series of small-scale proof of principle silage experiments were performed with fresh ryegrass. Having established that significant biochemical changes occur over an ensilage period as short as 2 days, we performed a series of experiments in which we used 50 silage additive combinations (prepared by using eight bacterial and other additives, each of which was added at six different levels, including zero [i.e., no additive]). The decrease in pH, the increase in lactate concentration, and the free amino acid concentration were measured after 2 days and used to calculate a “fitness” value that indicated the quality of the silage (compared to a control silage made without additives). This analysis also included a “cost” element to account for different total additive levels. In the initial experiment additive levels were selected randomly, but subsequently a genetic algorithm program was used to suggest new additive combinations based on the fitness values determined in the preceding experiments. The result was very efficient selection for silages in which large decreases in pH and high levels of lactate occurred along with low levels of free amino acids. During the series of five experiments, each of which comprised 50 treatments, there was a steady increase in the amount of lactate that accumulated; the best treatment combination was that used in the last experiment, which produced 4.6 times more lactate than the untreated silage. The additive combinations that were found to yield the highest fitness values in the final (fifth) experiment were assessed to determine a range of biochemical and microbiological quality parameters during full-term silage
Additive genetic effect of APOE and BDNF on hippocampus activity.
Kauppi, Karolina; Nilsson, Lars-Göran; Persson, Jonas; Nyberg, Lars
2014-04-01
Human memory is a highly heritable polygenic trait with complex inheritance patterns. To study the genetics of memory and memory-related diseases, hippocampal functioning has served as an intermediate phenotype. The importance of investigating gene-gene effects on complex phenotypes has been emphasized, but most imaging studies still focus on single polymorphisms. APOE ε4 and BDNF Met, two of the most studied gene variants for variability in memory performance and neuropsychiatric disorders, have both separately been related to poorer episodic memory and altered hippocampal functioning. Here, we investigated the combined effect of APOE and BDNF on hippocampal activation (N=151). No non-additive interaction effects were seen. Instead, the results revealed decreased activation in bilateral hippocampus and parahippocampus as a function of the number of APOE ε4 and BDNF Met alleles present (neither, one, or both). The combined effect was stronger than either of the individual effects, and both gene variables explained significant proportions of variance in BOLD signal change. Thus, there was an additive gene-gene effect of APOE and BDNF on medial temporal lobe (MTL) activation, showing that a larger proportion of variance in brain activation attributed to genetics can be explained by considering more than one gene variant. This effect might be relevant for the understanding of normal variability in memory function as well as memory-related disorders associated with APOE and BDNF. PMID:24321557
NASA Astrophysics Data System (ADS)
Dehipawala, Sunil; Nguyen, A.; Tremberger, G.; Cheung, E.; Holden, T.; Lieberman, D.; Cheung, T.
2013-09-01
The evolutionary rate co-variation in meiotic proteins has been reported for yeast and mammal using phylogenic branch lengths which assess retention, duplication and mutation. The bioinformatics of the corresponding DNA sequences could be classified as a diagram of fractal dimension and Shannon entropy. Results from biomedical gene research provide examples on the diagram methodology. The identification of adaptive selection using entropy marker and functional-structural diversity using fractal dimension would support a regression analysis where the coefficient of determination would serve as evolutionary pathway marker for DNA sequences and be an important component in the astrobiology community. Comparisons between biomedical genes such as EEF2 (elongation factor 2 human, mouse, etc), WDR85 in epigenetics, HAR1 in human specificity, clinical trial targeted cancer gene CD47, SIRT6 in spermatogenesis, and HLA-C in mosquito bite immunology demonstrate the diagram classification methodology. Comparisons to the SEPT4-XIAP pair in stem cell apoptosis, testesexpressed taste genes TAS1R3-GNAT3 pair, and amyloid beta APLP1-APLP2 pair with the yeast-mammal DNA sequences for meiotic proteins RAD50-MRE11 pair and NCAPD2-ICK pair have accounted for the observed fluctuating evolutionary pressure systematically. Regression with high R-sq values or a triangular-like cluster pattern for concordant pairs in co-variation among the studied species could serve as evidences for the possible location of common ancestors in the entropy-fractal dimension diagram, consistent with an example of the human-chimp common ancestor study using the FOXP2 regulated genes reported in human fetal brain study. The Deinococcus radiodurans R1 Rad-A could be viewed as an outlier in the RAD50 diagram and also in the free energy versus fractal dimension regression Cook's distance, consistent with a non-Earth source for this radiation resistant bacterium. Convergent and divergent fluctuating evolutionary
NASA Astrophysics Data System (ADS)
Chartin, Caroline; Stevens, Antoine; van Wesemael, Bas
2015-04-01
Providing spatially continuous Soil Organic Carbon data (SOC) is needed to support decisions regarding soil management, and inform the political debate with quantified estimates of the status and change of the soil resource. Digital Soil Mapping techniques are based on relations existing between a soil parameter (measured at different locations in space at a defined period) and relevant covariates (spatially continuous data) that are factors controlling soil formation and explaining the spatial variability of the target variable. This study aimed at apply DSM techniques to recent SOC content measurements (2005-2013) in three different landuses, i.e. cropland, grassland, and forest, in the Walloon region (Southern Belgium). For this purpose, SOC databases of two regional Soil Monitoring Networks (CARBOSOL for croplands and grasslands, and IPRFW for forests) were first harmonized, totalising about 1,220 observations. Median values of SOC content for croplands, grasslands, and forests, are respectively of 12.8, 29.0, and 43.1 g C kg-1. Then, a set of spatial layers were prepared with a resolution of 40 meters and with the same grid topology, containing environmental covariates such as, landuses, Digital Elevation Model and its derivatives, soil texture, C factor, carbon inputs by manure, and climate. Here, in addition to the three classical texture classes (clays, silt, and sand), we tested the use of clays + fine silt content (particles < 20 µm and related to stable carbon fraction) as soil covariate explaining SOC variations. For each of the three land uses (cropland, grassland and forest), a Generalized Additive Model (GAM) was calibrated on two thirds of respective dataset. The remaining samples were assigned to a test set to assess model performance. A backward stepwise procedure was followed to select the relevant environmental covariates using their approximate p-values (the level of significance was set at p < 0.05). Standard errors were estimated for each of
Tatar, M.; Promislow, D.E.L.; Khazaeli, A.A.; Curtsinger, J.W.
1996-06-01
Under the mutation accumulation model of senescence, it was predicted that the additive genetic variance (V{sub A}) for fitness traits will increase with age. We measured age-specific mortality and fecundity from 65,134 Drosophila melanogaster and estimated genetic variance components, based on reciprocal crosses of extracted second chromosome lines. Elsewhere we report the results for mortality. Here, for fecundity, we report a biomodal pattern for V{sub A} with peaks at 3 days and at 17-31 days. Under the antagonistic pleiotropy model of senescence, it was predicted that negative correlations will exist between early and late life history traits. For fecundity itself we find positive genetic correlations among age classes >3 days but negative nonsignificant correlations between fecundity at 3 days and at older age classes. For fecundity vs. age-specific mortality, we find positive fitness correlations (negative genetic correlations) among the traits at all ages >3 days but a negative fitness correlation between fecundity at 3 days and mortality at the oldest ages (positive genetic correlations). For age-specific mortality itself we find overwhelmingly positive genetic correlations among all age classes. The data suggest that mutation accumulation may be a major source of standing genetic variance for senescence. 75 refs., 4 figs., 1 tab.
Tatar, M.; Promislow, DEL.; Khazaeli, A. A.; Curtsinger, J. W.
1996-01-01
Under the mutation accumulation model of senescence, it was predicted that the additive genetic variance (V(A)) for fitness traits will increase with age. We measured age-specific mortality and fecundity from 65,134 Drosophila melanogaster and estimated genetic variance components, based on reciprocal crosses of extracted second chromosome lines. Elsewhere we report the results for mortality. Here, for fecundity, we report a bimodal pattern for V(A) with peaks at 3 days and at 17-31 days. Under the antagonistic pleiotropy model of senescence, it was predicted that negative correlations will exist between early and late life history traits. For fecundity itself we find positive genetic correlations among age classes >3 days but negative nonsignificant correlations between fecundity at 3 days and at older age classes. For fecundity vs. age-specific mortality, we find positive fitness correlations (negative genetic correlations) among the traits at all ages >3 days but a negative fitness correlation between fecundity at 3 days and mortality at the oldest ages (positive genetic correlations). For age-specific mortality itself we find overwhelmingly positive genetic correlations among all age classes. The data suggest that mutation accumulation may be a major source of standing genetic variance for senescence. PMID:8725233
NASA Astrophysics Data System (ADS)
Kisil, Vladimir V.
2011-03-01
Dedicated to the memory of Cora Sadosky The paper develops theory of covariant transform, which is inspired by the wavelet construction. It was observed that many interesting types of wavelets (or coherent states) arise from group representations which are not square integrable or vacuum vectors which are not admissible. Covariant transform extends an applicability of the popular wavelets construction to classic examples like the Hardy space H2, Banach spaces, covariant functional calculus and many others.
Galilean covariant harmonic oscillator
NASA Technical Reports Server (NTRS)
Horzela, Andrzej; Kapuscik, Edward
1993-01-01
A Galilean covariant approach to classical mechanics of a single particle is described. Within the proposed formalism, all non-covariant force laws defining acting forces which become to be defined covariantly by some differential equations are rejected. Such an approach leads out of the standard classical mechanics and gives an example of non-Newtonian mechanics. It is shown that the exactly solvable linear system of differential equations defining forces contains the Galilean covariant description of harmonic oscillator as its particular case. Additionally, it is demonstrated that in Galilean covariant classical mechanics the validity of the second Newton law of dynamics implies the Hooke law and vice versa. It is shown that the kinetic and total energies transform differently with respect to the Galilean transformations.
Greenwood, Tiffany A; Lazzeroni, Laura C; Calkins, Monica E; Freedman, Robert; Green, Michael F; Gur, Raquel E; Gur, Ruben C; Light, Gregory A; Nuechterlein, Keith H; Olincy, Ann; Radant, Allen D; Seidman, Larry J; Siever, Larry J; Silverman, Jeremy M; Stone, William S; Sugar, Catherine A; Swerdlow, Neal R; Tsuang, Debby W; Tsuang, Ming T; Turetsky, Bruce I; Braff, David L
2016-01-01
The Consortium on the Genetics of Schizophrenia Family Study (COGS-1) has previously reported our efforts to characterize the genetic architecture of 12 primary endophenotypes for schizophrenia. We now report the characterization of 13 additional measures derived from the same endophenotype test paradigms in the COGS-1 families. Nine of the measures were found to discriminate between schizophrenia patients and controls, were significantly heritable (31 to 62%), and were sufficiently independent of previously assessed endophenotypes, demonstrating utility as additional endophenotypes. Genotyping via a custom array of 1536 SNPs from 94 candidate genes identified associations for CTNNA2, ERBB4, GRID1, GRID2, GRIK3, GRIK4, GRIN2B, NOS1AP, NRG1, and RELN across multiple endophenotypes. An experiment-wide p value of 0.003 suggested that the associations across all SNPs and endophenotypes collectively exceeded chance. Linkage analyses performed using a genome-wide SNP array further identified significant or suggestive linkage for six of the candidate endophenotypes, with several genes of interest located beneath the linkage peaks (e.g., CSMD1, DISC1, DLGAP2, GRIK2, GRIN3A, and SLC6A3). While the partial convergence of the association and linkage likely reflects differences in density of gene coverage provided by the distinct genotyping platforms, it is also likely an indication of the differential contribution of rare and common variants for some genes and methodological differences in detection ability. Still, many of the genes implicated by COGS through endophenotypes have been identified by independent studies of common, rare, and de novo variation in schizophrenia, all converging on a functional genetic network related to glutamatergic neurotransmission that warrants further investigation. PMID:26597662
Additive genetic contribution to symptom dimensions in major depressive disorder.
Pearson, Rahel; Palmer, Rohan H C; Brick, Leslie A; McGeary, John E; Knopik, Valerie S; Beevers, Christopher G
2016-05-01
Major depressive disorder (MDD) is a phenotypically heterogeneous disorder with a complex genetic architecture. In this study, genomic-relatedness-matrix restricted maximum-likelihood analysis (GREML) was used to investigate the extent to which variance in depression symptoms/symptom dimensions can be explained by variation in common single nucleotide polymorphisms (SNPs) in a sample of individuals with MDD (N = 1,558) who participated in the National Institute of Mental Health Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. A principal components analysis of items from the Hamilton Rating Scale for Depression (HRSD) obtained prior to treatment revealed 4 depression symptom components: (a) appetite, (b) core depression symptoms (e.g., depressed mood, anhedonia), (c) insomnia, and (d) anxiety. These symptom dimensions were associated with SNP-based heritability (hSNP2) estimates of 30%, 14%, 30%, and 5%, respectively. Results indicated that the genetic contribution of common SNPs to depression symptom dimensions were not uniform. Appetite and insomnia symptoms in MDD had a relatively strong genetic contribution whereas the genetic contribution was relatively small for core depression and anxiety symptoms. While in need of replication, these results suggest that future gene discovery efforts may strongly benefit from parsing depression into its constituent parts. (PsycINFO Database Record PMID:27124715
Prevalence of gene expression additivity in genetically stable wheat allohexaploids.
Chelaifa, Houda; Chagué, Véronique; Chalabi, Smahane; Mestiri, Imen; Arnaud, Dominique; Deffains, Denise; Lu, Yunhai; Belcram, Harry; Huteau, Virginie; Chiquet, Julien; Coriton, Olivier; Just, Jérémy; Jahier, Joseph; Chalhoub, Boulos
2013-02-01
The reprogramming of gene expression appears as the major trend in synthetic and natural allopolyploids where expression of an important proportion of genes was shown to deviate from that of the parents or the average of the parents. In this study, we analyzed gene expression changes in previously reported, highly stable synthetic wheat allohexaploids that combine the D genome of Aegilops tauschii and the AB genome extracted from the natural hexaploid wheat Triticum aestivum. A comprehensive genome-wide analysis of transcriptional changes using the Affymetrix GeneChip Wheat Genome Array was conducted. Prevalence of gene expression additivity was observed where expression does not deviate from the average of the parents for 99.3% of 34,820 expressed transcripts. Moreover, nearly similar expression was observed (for 99.5% of genes) when comparing these synthetic and natural wheat allohexaploids. Such near-complete additivity has never been reported for other allopolyploids and, more interestingly, for other synthetic wheat allohexaploids that differ from the ones studied here by having the natural tetraploid Triticum turgidum as the AB genome progenitor. Our study gave insights into the dynamics of additive gene expression in the highly stable wheat allohexaploids. PMID:23278496
Lohr, Jennifer N; Haag, Christoph R
2015-12-01
Reduced population size is thought to have strong consequences for evolutionary processes as it enhances the strength of genetic drift. In its interaction with selection, this is predicted to increase the genetic load, reduce inbreeding depression, and increase hybrid vigor, and in turn affect phenotypic evolution. Several of these predictions have been tested, but comprehensive studies controlling for confounding factors are scarce. Here, we show that populations of Daphnia magna, which vary strongly in genetic diversity, also differ in genetic load, inbreeding depression, and hybrid vigor in a way that strongly supports theoretical predictions. Inbreeding depression is positively correlated with genetic diversity (a proxy for Ne ), and genetic load and hybrid vigor are negatively correlated with genetic diversity. These patterns remain significant after accounting for potential confounding factors and indicate that, in small populations, a large proportion of the segregation load is converted into fixed load. Overall, the results suggest that the nature of genetic variation for fitness-related traits differs strongly between large and small populations. This has large consequences for evolutionary processes in natural populations, such as selection on dispersal, breeding systems, ageing, and local adaptation. PMID:26497949
Forest, Adriana R; Semeniuk, Christina A D; Heath, Daniel D; Pitcher, Trevor E
2016-08-01
Chinook salmon, Oncorhynchus tshawytscha, exhibit alternative reproductive tactics (ARTs) where males exist in two phenotypes: large "hooknose" males and smaller "jacks" that reach sexual maturity after only 1 year in seawater. The mechanisms that determine "jacking rate"-the rate at which males precociously sexually mature-are known to involve both genetics and differential growth rates, where individuals that become jacks exhibit higher growth earlier in life. The additive genetic components have been studied and it is known that jack sires produce significantly more jack offspring than hooknose sires, and vice versa. The current study was the first to investigate both additive and non-additive genetic components underlying jacking through the use of a full-factorial breeding design using all hooknose sires. The effect of dams and sires descendant from a marker-assisted broodstock program that identified "high performance" and "low performance" lines using growth- and survival-related gene markers was also studied. Finally, the relative growth of jack, hooknose, and female offspring was examined. No significant dam, sire, or interaction effects were observed in this study, and the maternal, additive, and non-additive components underlying jacking were small. Differences in jacking rates in this study were determined by dam performance line, where dams that originated from the low performance line produced significantly more jacks. Jack offspring in this study had a significantly larger body size than both hooknose males and females starting 1 year post-fertilization. This study provides novel information regarding the genetic architecture underlying ARTs in Chinook salmon that could have implications for the aquaculture industry, where jacks are not favoured due to their small body size and poor flesh quality. PMID:27450674
Fine-mapping in the MHC region accounts for 18% additional genetic risk for celiac disease
Gutierrez-Achury, Javier; Zhernakova, Alexandra; Pulit, Sara L.; Trynka, Gosia; Hunt, Karen A.; Romanos, Jihane; Raychaudhuri, Soumya; van Heel, David A.; Wijmenga, Cisca; de Bakker, Paul I.W.
2015-01-01
Although dietary gluten is the trigger, celiac disease risk is strongly influenced by genetic variation in the major histocompatibility complex (MHC) region. We fine-mapped the MHC association signal to identify additional risk factors independent of the HLA-DQ alleles and observed five novel associations that account for 18% of the genetic risk. Together with the 57 known non-MHC loci, genetic variation can now explain up to 48% of celiac disease heritability. PMID:25894500
ERIC Educational Resources Information Center
Miller, Geoffrey F.; Penke, Lars
2007-01-01
Most theories of human mental evolution assume that selection favored higher intelligence and larger brains, which should have reduced genetic variance in both. However, adult human intelligence remains highly heritable, and is genetically correlated with brain size. This conflict might be resolved by estimating the coefficient of additive genetic…
ERIC Educational Resources Information Center
Roisman, Glenn I.; Fraley, R. Chris
2008-01-01
A number of relatively small-sample, genetically sensitive studies of infant attachment security have been published in the past several years that challenge the view that all psychological phenotypes are heritable and that environmental influences on child development--to the extent that they can be detected--serve to make siblings dissimilar.…
Leamy, Larry J; Elo, Kari; Nielsen, Merlyn K; Van Vleck, L Dale; Pomp, Daniel
2005-01-01
We estimated heritabilities and genetic correlations for a suite of 15 characters in five functional groups in an advanced intercross population of over 2000 mice derived from a cross of inbred lines selected for high and low heat loss. Heritabilities averaged 0.56 for three body weights, 0.23 for two energy balance characters, 0.48 for three bone characters, 0.35 for four measures of adiposity, and 0.27 for three organ weights, all of which were generally consistent in magnitude with estimates derived in previous studies. Genetic correlations varied from -0.65 to +0.98, and were higher within these functional groups than between groups. These correlations generally conformed to a priori expectations, being positive in sign for energy expenditure and consumption (+0.24) and negative in sign for energy expenditure and adiposity (-0.17). The genetic correlations of adiposity with body weight at 3, 6, and 12 weeks of age (-0.29, -0.22, -0.26) all were negative in sign but not statistically significant. The independence of body weight and adiposity suggests that this advanced intercross population is ideal for a comprehensive discovery of genes controlling regulation of mammalian adiposity that are distinct from those for body weight. PMID:16194522
Mulligan, Megan K; Wang, Xusheng; Adler, Adrienne L; Mozhui, Khyobeni; Lu, Lu; Williams, Robert W
2012-01-01
GABA type-A receptors are essential for fast inhibitory neurotransmission and are critical in brain function. Surprisingly, expression of receptor subunits is highly variable among individuals, but the cause and impact of this fluctuation remains unknown. We have studied sources of variation for all 19 receptor subunits using massive expression data sets collected across multiple brain regions and platforms in mice and humans. Expression of Gabra1, Gabra2, Gabrb2, Gabrb3, and Gabrg2 is highly variable and heritable among the large cohort of BXD strains derived from crosses of fully sequenced parents--C57BL/6J and DBA/2J. Genetic control of these subunits is complex and highly dependent on tissue and mRNA region. Remarkably, this high variation is generally not linked to phenotypic differences. The single exception is Gabrb3, a locus that is linked to anxiety. We identified upstream genetic loci that influence subunit expression, including three unlinked regions of chromosome 5 that modulate the expression of nine subunits in hippocampus, and that are also associated with multiple phenotypes. Candidate genes within these loci include, Naaa, Nos1, and Zkscan1. We confirmed a high level of coexpression for subunits comprising the major channel--Gabra1, Gabrb2, and Gabrg2--and identified conserved members of this expression network in mice and humans. Gucy1a3, Gucy1b3, and Lis1 are novel and conserved associates of multiple subunits that are involved in inhibitory signaling. Finally, proximal and distal regions of the 3' UTRs of single subunits have remarkably independent expression patterns in both species. However, corresponding regions of different subunits often show congruent genetic control and coexpression (proximal-to-proximal or distal-to-distal), even in the absence of sequence homology. Our findings identify novel sources of variation that modulate subunit expression and highlight the extraordinary capacity of biological networks to buffer 4-100 fold
Porto, A; Sebastião, H; Pavan, S E; VandeBerg, J L; Marroig, G; Cheverud, J M
2015-04-01
We tested the hypothesis that the rate of marsupial cranial evolution is dependent on the distribution of genetic variation in multivariate space. To do so, we carried out a genetic analysis of cranial morphological variation in laboratory strains of Monodelphis domestica and used estimates of genetic covariation to analyse the morphological diversification of the Monodelphis brevicaudata species group. We found that within-species genetic variation is concentrated in only a few axes of the morphospace and that this strong genetic covariation influenced the rate of morphological diversification of the brevicaudata group, with between-species divergence occurring fastest when occurring along the genetic line of least resistance. Accounting for the geometric distribution of genetic variation also increased our ability to detect the selective regimen underlying species diversification, with several instances of selection only being detected when genetic covariances were taken into account. Therefore, this work directly links patterns of genetic covariation among traits to macroevolutionary patterns of morphological divergence. Our findings also suggest that the limited distribution of Monodelphis species in morphospace is the result of a complex interplay between the limited dimensionality of available genetic variation and strong stabilizing selection along two major axes of genetic variation. PMID:25818173
Porto, Arthur; Sebastião, Harley; Pavan, Silvia Eliza; VandeBerg, John L.; Marroig, Gabriel; Cheverud, James M.
2015-01-01
We tested the hypothesis that the rate of marsupial cranial evolution is dependent on the distribution of genetic variation in multivariate space. To do so, we carried out a genetic analysis of cranial morphological variation in laboratory strains of Monodelphis domestica and used estimates of genetic covariation to analyze the morphological diversification of the Monodelphis brevicaudata species group. We found that within-species genetic variation is concentrated in only a few axes of the morphospace and that this strong genetic covariation influenced the rate of morphological diversification of the brevicaudata group, with between-species divergence occurring fastest when occurring along the genetic line of least resistance. Accounting for the geometric distribution of genetic variation also increased our ability to detect the selective regimen underlying species diversification, with several instances of selection only being detected when genetic covariances were taken into account. Therefore, this work directly links patterns of genetic covariation among traits to macroevolutionary patterns of morphological divergence. Our findings also suggest that the limited distribution of Monodelphis species in morphospace is the result of a complex interplay between the limited dimensionality of available genetic variation and strong stabilizing selection along two major axes of genetic variation. PMID:25818173
Estimation of Additive, Dominance, and Imprinting Genetic Variance Using Genomic Data
Lopes, Marcos S.; Bastiaansen, John W. M.; Janss, Luc; Knol, Egbert F.; Bovenhuis, Henk
2015-01-01
Traditionally, exploration of genetic variance in humans, plants, and livestock species has been limited mostly to the use of additive effects estimated using pedigree data. However, with the development of dense panels of single-nucleotide polymorphisms (SNPs), the exploration of genetic variation of complex traits is moving from quantifying the resemblance between family members to the dissection of genetic variation at individual loci. With SNPs, we were able to quantify the contribution of additive, dominance, and imprinting variance to the total genetic variance by using a SNP regression method. The method was validated in simulated data and applied to three traits (number of teats, backfat, and lifetime daily gain) in three purebred pig populations. In simulated data, the estimates of additive, dominance, and imprinting variance were very close to the simulated values. In real data, dominance effects account for a substantial proportion of the total genetic variance (up to 44%) for these traits in these populations. The contribution of imprinting to the total phenotypic variance of the evaluated traits was relatively small (1–3%). Our results indicate a strong relationship between additive variance explained per chromosome and chromosome length, which has been described previously for other traits in other species. We also show that a similar linear relationship exists for dominance and imprinting variance. These novel results improve our understanding of the genetic architecture of the evaluated traits and shows promise to apply the SNP regression method to other traits and species, including human diseases. PMID:26438289
López-Aumatell, Regina; Martínez-Membrives, Esther; Vicens-Costa, Elia; Cañete, Toni; Blázquez, Gloria; Mont-Cardona, Carme; Johannesson, Martina; Flint, Jonathan; Tobeña, Adolf; Fernández-Teruel, Alberto
2011-01-01
Physiological and environmental variables, or covariates, can account for an important portion of the variability observed in behavioural/physiological results from different laboratories even when using the same type of animals and phenotyping procedures. We present the results of a behavioural study with a sample of 1456 genetically heterogeneous N/Nih-HS rats, including males and females, which are part of a larger genome-wide fine-mapping QTL (Quantitative Trait Loci) study. N/Nih-HS rats have been derived from 8 inbred strains and provide very small distance between genetic recombinations, which makes them a unique tool for fine-mapping QTL studies. The behavioural test battery comprised the elevated zero-maze test for anxiety, novel-cage (open-field like) activity, two-way active avoidance acquisition (related to conditioned anxiety) and context-conditioned freezing (i.e. classically conditioned fear). Using factorial analyses of variance (ANOVAs) we aimed to analyse sex differences in anxiety and fear in this N/Nih-HS rat sample, as well as to assess the effects of (and interactions with) other independent factors, such as batch, season, coat colour and experimenter. Body weight was taken as a quantitative covariate and analysed by covariance analysis (ANCOVA). Obliquely-rotated factor analyses were also performed separately for each sex, in order to evaluate associations among the most relevant variables from each behavioural test and the common dimensions (i.e. factors) underlying the different behavioural responses. ANOVA analyses showed a consistent pattern of sex effects, with females showing less signs of anxiety and fear than males across all tests. There were also significant main effects of batch, season, colour and experimenter on almost all behavioural variables, as well as "sex × batch", "sex × season" and "sex × experimenter" interactions. Body weight showed significant effects in the ANCOVAs of most behavioural measures, but sex effects were
[Food additives and genetically modified food--a risk for allergic patients?].
Wüthrich, B
1999-04-01
Adverse reactions to food and food additives must be classified according to pathogenic criteria. It is necessary to strictly differentiate between an allergy, triggered by a substance-specific immunological mechanism, and an intolerance, in which no specific immune reaction can be established. In contrast to views expressed in the media, by laymen and patients, adverse reactions to additives are less frequent than is believed. Due to frequently "alternative" methods of examination, an allergy to food additives is often wrongly blamed as the cause of a wide variety of symptoms and illness. Diagnosing an allergy or intolerance to additives normally involves carrying out double-blind, placebo-controlled oral provocation tests with food additives. Allergic reactions to food additives occur particularly against additives which are organic in origin. In principle, it is possible that during the manufacture of genetically modified plants and food, proteins are transferred which potentially create allergies. However, legislation exists both in the USA (Federal Drug Administration, FDA) and in Switzerland (Ordinance on the approval process for GM food, GM food additives and GM accessory agents for processing) which require a careful analysis before a genetically modified product is launched, particularly where foreign genes are introduced. Products containing genetically modified organisms (GMO) as additives must be declared. In addition, the source of the foreign protein must be identified. The "Round-up ready" (RR) soya flour introduced in Switzerland is no different from natural soya flour in terms of its allergenic potential. Genetically modified food can be a blessing for allergic individuals if gene technology were to succeed in removing the allergen (e.g. such possibilities exist for rice). The same caution shown towards genetically modified food might also be advisable for foreign food in our diet. Luckily, the immune system of the digestive tract in healthy people
Genetic interactions contribute less than additive effects to quantitative trait variation in yeast
Bloom, Joshua S.; Kotenko, Iulia; Sadhu, Meru J.; Treusch, Sebastian; Albert, Frank W.; Kruglyak, Leonid
2015-01-01
Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTL–QTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL–QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies. PMID:26537231
Technology Transfer Automated Retrieval System (TEKTRAN)
A method of accounting for differences in variation in components of test-day milk production records was developed. This method could improve the accuracy of genetic evaluations. A random regression model is used to analyze the data, then a transformation is applied to the random regression coeffic...
Common genetic variants, acting additively, are a major source of risk for autism
2012-01-01
Background Autism spectrum disorders (ASD) are early onset neurodevelopmental syndromes typified by impairments in reciprocal social interaction and communication, accompanied by restricted and repetitive behaviors. While rare and especially de novo genetic variation are known to affect liability, whether common genetic polymorphism plays a substantial role is an open question and the relative contribution of genes and environment is contentious. It is probable that the relative contributions of rare and common variation, as well as environment, differs between ASD families having only a single affected individual (simplex) versus multiplex families who have two or more affected individuals. Methods By using quantitative genetics techniques and the contrast of ASD subjects to controls, we estimate what portion of liability can be explained by additive genetic effects, known as narrow-sense heritability. We evaluate relatives of ASD subjects using the same methods to evaluate the assumptions of the additive model and partition families by simplex/multiplex status to determine how heritability changes with status. Results By analyzing common variation throughout the genome, we show that common genetic polymorphism exerts substantial additive genetic effects on ASD liability and that simplex/multiplex family status has an impact on the identified composition of that risk. As a fraction of the total variation in liability, the estimated narrow-sense heritability exceeds 60% for ASD individuals from multiplex families and is approximately 40% for simplex families. By analyzing parents, unaffected siblings and alleles not transmitted from parents to their affected children, we conclude that the data for simplex ASD families follow the expectation for additive models closely. The data from multiplex families deviate somewhat from an additive model, possibly due to parental assortative mating. Conclusions Our results, when viewed in the context of results from genome
45 CFR 146.122 - Additional requirements prohibiting discrimination based on genetic information.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 45 Public Welfare 1 2011-10-01 2011-10-01 false Additional requirements prohibiting discrimination based on genetic information. 146.122 Section 146.122 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS REQUIREMENTS FOR THE GROUP HEALTH INSURANCE MARKET Requirements Relating to Access...
Code of Federal Regulations, 2014 CFR
2014-04-01
... 26 Internal Revenue 17 2014-04-01 2014-04-01 false Additional requirements prohibiting discrimination based on genetic information (temporary). 54.9802-3T Section 54.9802-3T Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) MISCELLANEOUS EXCISE TAXES (CONTINUED) PENSION EXCISE TAXES § 54.9802-3T...
29 CFR 2590.702-1 - Additional requirements prohibiting discrimination based on genetic information.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 29 Labor 9 2014-07-01 2014-07-01 false Additional requirements prohibiting discrimination based on genetic information. 2590.702-1 Section 2590.702-1 Labor Regulations Relating to Labor (Continued) EMPLOYEE BENEFITS SECURITY ADMINISTRATION, DEPARTMENT OF LABOR GROUP HEALTH PLANS RULES AND REGULATIONS FOR GROUP HEALTH PLANS Health...
Code of Federal Regulations, 2012 CFR
2012-04-01
... 26 Internal Revenue 17 2012-04-01 2012-04-01 false Additional requirements prohibiting discrimination based on genetic information (temporary). 54.9802-3T Section 54.9802-3T Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) MISCELLANEOUS EXCISE TAXES (CONTINUED) PENSION EXCISE TAXES § 54.9802-3T...
Code of Federal Regulations, 2013 CFR
2013-04-01
... 26 Internal Revenue 17 2013-04-01 2013-04-01 false Additional requirements prohibiting discrimination based on genetic information (temporary). 54.9802-3T Section 54.9802-3T Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) MISCELLANEOUS EXCISE TAXES (CONTINUED) PENSION EXCISE TAXES § 54.9802-3T...
NASA Technical Reports Server (NTRS)
Smalheer, C. V.
1973-01-01
The chemistry of lubricant additives is discussed to show what the additives are chemically and what functions they perform in the lubrication of various kinds of equipment. Current theories regarding the mode of action of lubricant additives are presented. The additive groups discussed include the following: (1) detergents and dispersants, (2) corrosion inhibitors, (3) antioxidants, (4) viscosity index improvers, (5) pour point depressants, and (6) antifouling agents.
McGuigan, Katrina; Aguirre, J David; Blows, Mark W
2015-11-01
How new mutations contribute to genetic variation is a key question in biology. Although the evolutionary fate of an allele is largely determined by its heterozygous effect, most estimates of mutational variance and mutational effects derive from highly inbred lines, where new mutations are present in homozygous form. In an attempt to overcome this limitation, middle-class neighborhood (MCN) experiments have been used to assess the fitness effect of new mutations in heterozygous form. However, because MCN populations harbor substantial standing genetic variance, estimates of mutational variance have not typically been available from such experiments. Here we employ a modification of the animal model to analyze data from 22 generations of Drosophila serrata bred in an MCN design. Mutational heritability, measured for eight cuticular hydrocarbons, 10 wing-shape traits, and wing size in this outbred genetic background, ranged from 0.0006 to 0.006 (with one exception), a similar range to that reported from studies employing inbred lines. Simultaneously partitioning the additive and mutational variance in the same outbred population allowed us to quantitatively test the ability of mutation-selection balance models to explain the observed levels of additive and mutational genetic variance. The Gaussian allelic approximation and house-of-cards models, which assume real stabilizing selection on single traits, both overestimated the genetic variance maintained at equilibrium, but the house-of-cards model was a closer fit to the data. This analytical approach has the potential to be broadly applied, expanding our understanding of the dynamics of genetic variance in natural populations. PMID:26384357
Vrshek-Schallhorn, Suzanne; Stroud, Catherine B; Mineka, Susan; Zinbarg, Richard E; Adam, Emma K; Redei, Eva E; Hammen, Constance; Craske, Michelle G
2015-11-01
Behavioral genetic research supports polygenic models of depression in which many genetic variations each contribute a small amount of risk, and prevailing diathesis-stress models suggest gene-environment interactions (G×E). Multilocus profile scores of additive risk offer an approach that is consistent with polygenic models of depression risk. In a first demonstration of this approach in a G×E predicting depression, we created an additive multilocus profile score from 5 serotonin system polymorphisms (1 each in the genes HTR1A, HTR2A, HTR2C, and 2 in TPH2). Analyses focused on 2 forms of interpersonal stress as environmental risk factors. Using 5 years of longitudinal diagnostic and life stress interviews from 387 emerging young adults in the Youth Emotion Project, survival analyses show that this multilocus profile score interacts with major interpersonal stressful life events to predict major depressive episode onsets (hazard ratio [HR] = 1.815, p = .007). Simultaneously, there was a significant protective effect of the profile score without a recent event (HR = 0.83, p = .030). The G×E effect with interpersonal chronic stress was not significant (HR = 1.15, p = .165). Finally, effect sizes for genetic factors examined ignoring stress suggested such an approach could lead to overlooking or misinterpreting genetic effects. Both the G×E effect and the protective simple main effect were replicated in a sample of early adolescent girls (N = 105). We discuss potential benefits of the multilocus genetic profile score approach and caveats for future research. PMID:26595467
Gasparini, Clelia; Devigili, Alessandro; Dosselli, Ryan; Pilastro, Andrea
2013-01-01
In polyandrous species, a male's reproductive success depends on his fertilization capability and traits enhancing competitive fertilization success will be under strong, directional selection. This leads to the prediction that these traits should show stronger condition dependence and larger genetic variance than other traits subject to weaker or stabilizing selection. While empirical evidence of condition dependence in postcopulatory traits is increasing, the comparison between sexually selected and ‘control’ traits is often based on untested assumption concerning the different strength of selection acting on these traits. Furthermore, information on selection in the past is essential, as both condition dependence and genetic variance of a trait are likely to be influenced by the pattern of selection acting historically on it. Using the guppy (Poecilia reticulata), a livebearing fish with high levels of multiple paternity, we performed three independent experiments on three ejaculate quality traits, sperm number, velocity, and size, which have been previously shown to be subject to strong, intermediate, and weak directional postcopulatory selection, respectively. First, we conducted an inbreeding experiment to determine the pattern of selection in the past. Second, we used a diet restriction experiment to estimate their level of condition dependence. Third, we used a half-sib/full-sib mating design to estimate the coefficients of additive genetic variance (CVA) underlying these traits. Additionally, using a simulated predator evasion test, we showed that both inbreeding and diet restriction significantly reduced condition. According to predictions, sperm number showed higher inbreeding depression, stronger condition dependence, and larger CVA than sperm velocity and sperm size. The lack of significant genetic correlation between sperm number and velocity suggests that the former may respond to selection independently one from other ejaculate quality traits
de Candia, Teresa R.; Lee, S. Hong; Yang, Jian; Browning, Brian L.; Gejman, Pablo V.; Levinson, Douglas F.; Mowry, Bryan J.; Hewitt, John K.; Goddard, Michael E.; O’Donovan, Michael C.; Purcell, Shaun M.; Posthuma, Danielle; Visscher, Peter M.; Wray, Naomi R.; Keller, Matthew C.
2013-01-01
To investigate the extent to which the proportion of schizophrenia’s additive genetic variation tagged by SNPs is shared by populations of European and African descent, we analyzed the largest combined African descent (AD [n = 2,142]) and European descent (ED [n = 4,990]) schizophrenia case-control genome-wide association study (GWAS) data set available, the Molecular Genetics of Schizophrenia (MGS) data set. We show how a method that uses genomic similarities at measured SNPs to estimate the additive genetic correlation (SNP correlation [SNP-rg]) between traits can be extended to estimate SNP-rg for the same trait between ethnicities. We estimated SNP-rg for schizophrenia between the MGS ED and MGS AD samples to be 0.66 (SE = 0.23), which is significantly different from 0 (p(SNP-rg = 0) = 0.0003), but not 1 (p(SNP-rg = 1) = 0.26). We re-estimated SNP-rg between an independent ED data set (n = 6,665) and the MGS AD sample to be 0.61 (SE = 0.21, p(SNP-rg = 0) = 0.0003, p(SNP-rg = 1) = 0.16). These results suggest that many schizophrenia risk alleles are shared across ethnic groups and predate African-European divergence. PMID:23954163
Wei, Jianwen; Flaherty, Stephen; Karsenty, Gerard
2016-01-01
Our knowledge of whole organism physiology has greatly advanced in the past decades through mouse genetics. In particular, genetic studies have revealed that most organs interact with one another through hormones in order to maintain normal physiological functions and the homeostasis of the entire organism. Remarkably, through these studies many unexpected novel endocrine means to regulate physiological functions have been uncovered. The skeletal system is one example. In this article, we review a series of studies that over the years have identified bone as an endocrine organ. The mechanism of action, pathological relevance, and therapeutic implications of the functions of the bone-derived hormone osteocalcin are discussed. In the last part of this review we discuss the possibility that additional endocrine functions of the skeleton may exist.
Kirkpatrick, Robert M.; McGue, Matt; Iacono, William G.
2015-01-01
The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES—an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research. PMID:25539975
Kirkpatrick, Robert M; McGue, Matt; Iacono, William G
2015-03-01
The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES-an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research. PMID:25539975
Effect of multiplicative and additive noise on genetic transcriptional regulatory mechanism
NASA Astrophysics Data System (ADS)
Liu, Xue-Mei; Xie, Hui-Zhang; Liu, Liang-Gang; Li, Zhi-Bing
2009-02-01
A multiplicative noise and an additive noise are introduced in the kinetic model of Smolen-Baxter-Byrne [P. Smolen, D.A. Baxter, J.H. Byrne, Amer. J. Physiol. Cell. Physiol. 274 (1998) 531], in which the expression of gene is controlled by protein concentration of transcriptional activator. The Fokker-Planck equation is solved and the steady-state probability distribution is obtained numerically. It is found that the multiplicative noise converts the bistability to monostability that can be regarded as a noise-induced transition. The additive noise reduces the transcription efficiency. The correlation between the multiplicative noise and the additive noise works as a genetic switch and regulates the gene transcription effectively.
Su, Junji; Zhang, Jinpeng; Song, Liqiang; Gao, Ainong; Yang, Xinming; Li, Xiuquan; Liu, Weihua; Li, Lihui
2014-01-01
Agropyron cristatum (L.) Gaertn. (2n = 4x = 28, PPPP) not only is cultivated as pasture fodder but also could provide many desirable genes for wheat improvement. It is critical to obtain common wheat–A. cristatum alien disomic addition lines to locate the desired genes on the P genome chromosomes. Comparative analysis of the homoeologous relationships between the P genome chromosome and wheat genome chromosomes is a key step in transferring different desirable genes into common wheat and producing the desired alien translocation line while compensating for the loss of wheat chromatin. In this study, six common wheat–A. cristatum disomic addition lines were produced and analyzed by phenotypic examination, genomic in situ hybridization (GISH), SSR markers from the ABD genomes and STS markers from the P genome. Comparative maps, six in total, were generated and demonstrated that all six addition lines belonged to homoeologous group 6. However, chromosome 6P had undergone obvious rearrangements in different addition lines compared with the wheat chromosome, indicating that to obtain a genetic compensating alien translocation line, one should recombine alien chromosomal regions with homoeologous wheat chromosomes. Indeed, these addition lines were classified into four types based on the comparative mapping: 6PI, 6PII, 6PIII, and 6PIV. The different types of chromosome 6P possessed different desirable genes. For example, the 6PI type, containing three addition lines, carried genes conferring high numbers of kernels per spike and resistance to powdery mildew, important traits for wheat improvement. These results may prove valuable for promoting the development of conventional chromosome engineering techniques toward molecular chromosome engineering. PMID:24595330
NASA Astrophysics Data System (ADS)
Edenhofer, Peter; Ulamec, Stephan
2015-04-01
The paper is devoted to results of doctoral research work at University of Bochum as applied to the radar transmission experiment CONSERT of the ESA cometary mission Rosetta. This research aims at achieving the limits of optimum spatial (and temporal) resolution for radar remote sensing by implementation of covariance informations concerned with error-balanced control as well as coherence of wave propagation effects through random composite media involved (based on Joel Franklin's approach of extended stochastic inversion). As a consequence the well-known inherent numerical instabilities of remote sensing are significantly reduced in a robust way by increasing the weight of main diagonal elements of the resulting composite matrix to be inverted with respect to off-diagonal elements following synergy relations as to the principle of correlation receiver in wireless telecommunications. It is shown that the enhancement of resolution for remote sensing holds for an integral and differential equation approach of inversion as well. In addition to that the paper presents a discussion on how the efficiency of inversion for radar data gets achieved by an overall optimization of inversion due to a novel neuro-genetic approach. Such kind of approach is in synergy with the priority research program "Organic Computing" of DFG / German Research Organization. This Neuro-Genetic Optimization (NGO) turns out, firstly, to take into account more detailed physical informations supporting further improved resolution such as the process of accretion for cometary nucleus, wave propagation effects from rough surfaces, ground clutter, nonlinear focusing, etc. as well as, secondly, to accelerate the computing process of inversion in a really significantly enhanced and fast way, e.g., enabling online-control of autonomous processes such as detection of unknown objects, navigation, etc. The paper describes in some detail how this neuro-genetic approach of optimization is incorporated into the
Travers, L M; Simmons, L W; Garcia-Gonzalez, F
2016-05-01
Polyandry is widespread despite its costs. The sexually selected sperm hypotheses ('sexy' and 'good' sperm) posit that sperm competition plays a role in the evolution of polyandry. Two poorly studied assumptions of these hypotheses are the presence of additive genetic variance in polyandry and sperm competitiveness. Using a quantitative genetic breeding design in a natural population of Drosophila melanogaster, we first established the potential for polyandry to respond to selection. We then investigated whether polyandry can evolve through sexually selected sperm processes. We measured lifetime polyandry and offensive sperm competitiveness (P2 ) while controlling for sampling variance due to male × male × female interactions. We also measured additive genetic variance in egg-to-adult viability and controlled for its effect on P2 estimates. Female lifetime polyandry showed significant and substantial additive genetic variance and evolvability. In contrast, we found little genetic variance or evolvability in P2 or egg-to-adult viability. Additive genetic variance in polyandry highlights its potential to respond to selection. However, the low levels of genetic variance in sperm competitiveness suggest that the evolution of polyandry may not be driven by sexy sperm or good sperm processes. PMID:26801640
McFarlane, S Eryn; Gorrell, Jamieson C; Coltman, David W; Humphries, Murray M; Boutin, Stan; McAdam, Andrew G
2014-01-01
A trait must genetically correlate with fitness in order to evolve in response to natural selection, but theory suggests that strong directional selection should erode additive genetic variance in fitness and limit future evolutionary potential. Balancing selection has been proposed as a mechanism that could maintain genetic variance if fitness components trade off with one another and has been invoked to account for empirical observations of higher levels of additive genetic variance in fitness components than would be expected from mutation–selection balance. Here, we used a long-term study of an individually marked population of North American red squirrels (Tamiasciurus hudsonicus) to look for evidence of (1) additive genetic variance in lifetime reproductive success and (2) fitness trade-offs between fitness components, such as male and female fitness or fitness in high- and low-resource environments. “Animal model” analyses of a multigenerational pedigree revealed modest maternal effects on fitness, but very low levels of additive genetic variance in lifetime reproductive success overall as well as fitness measures within each sex and environment. It therefore appears that there are very low levels of direct genetic variance in fitness and fitness components in red squirrels to facilitate contemporary adaptation in this population. PMID:24963372
NASA Technical Reports Server (NTRS)
Hepner, T. E.; Meyers, J. F. (Inventor)
1985-01-01
A laser velocimeter covariance processor which calculates the auto covariance and cross covariance functions for a turbulent flow field based on Poisson sampled measurements in time from a laser velocimeter is described. The device will process a block of data that is up to 4096 data points in length and return a 512 point covariance function with 48-bit resolution along with a 512 point histogram of the interarrival times which is used to normalize the covariance function. The device is designed to interface and be controlled by a minicomputer from which the data is received and the results returned. A typical 4096 point computation takes approximately 1.5 seconds to receive the data, compute the covariance function, and return the results to the computer.
A Covariance NMR Toolbox for MATLAB and OCTAVE
NASA Astrophysics Data System (ADS)
Short, Timothy; Alzapiedi, Leigh; Brüschweiler, Rafael; Snyder, David
2011-03-01
The Covariance NMR Toolbox is a new software suite that provides a streamlined implementation of covariance-based analysis of multi-dimensional NMR data. The Covariance NMR Toolbox uses the MATLAB or, alternatively, the freely available GNU OCTAVE computer language, providing a user-friendly environment in which to apply and explore covariance techniques. Covariance methods implemented in the toolbox described here include direct and indirect covariance processing, 4D covariance, generalized indirect covariance (GIC), and Z-matrix transform. In order to provide compatibility with a wide variety of spectrometer and spectral analysis platforms, the Covariance NMR Toolbox uses the NMRPipe format for both input and output files. Additionally, datasets small enough to fit in memory are stored as arrays that can be displayed and further manipulated in a versatile manner within MATLAB or OCTAVE.
A covariance NMR toolbox for MATLAB and OCTAVE.
Short, Timothy; Alzapiedi, Leigh; Brüschweiler, Rafael; Snyder, David
2011-03-01
The Covariance NMR Toolbox is a new software suite that provides a streamlined implementation of covariance-based analysis of multi-dimensional NMR data. The Covariance NMR Toolbox uses the MATLAB or, alternatively, the freely available GNU OCTAVE computer language, providing a user-friendly environment in which to apply and explore covariance techniques. Covariance methods implemented in the toolbox described here include direct and indirect covariance processing, 4D covariance, generalized indirect covariance (GIC), and Z-matrix transform. In order to provide compatibility with a wide variety of spectrometer and spectral analysis platforms, the Covariance NMR Toolbox uses the NMRPipe format for both input and output files. Additionally, datasets small enough to fit in memory are stored as arrays that can be displayed and further manipulated in a versatile manner within MATLAB or OCTAVE. PMID:21215669
45 CFR 146.122 - Additional requirements prohibiting discrimination based on genetic information.
Code of Federal Regulations, 2012 CFR
2012-10-01
... individual has a genetic variant associated with hereditary nonpolyposis colorectal cancer is a genetic test... manifested with respect to A. Example 2. (i) Facts. Individual B has several family members with colon cancer... hereditary nonpolyposis colorectal cancer (HNPCC). B's physician, a health care professional with...
45 CFR 146.122 - Additional requirements prohibiting discrimination based on genetic information.
Code of Federal Regulations, 2013 CFR
2013-10-01
... individual has a genetic variant associated with hereditary nonpolyposis colorectal cancer is a genetic test... manifested with respect to A. Example 2. (i) Facts. Individual B has several family members with colon cancer... hereditary nonpolyposis colorectal cancer (HNPCC). B's physician, a health care professional with...
45 CFR 146.122 - Additional requirements prohibiting discrimination based on genetic information.
Code of Federal Regulations, 2010 CFR
2010-10-01
... individual has a genetic variant associated with hereditary nonpolyposis colorectal cancer is a genetic test... manifested with respect to A. Example 2. (i) Facts. Individual B has several family members with colon cancer... hereditary nonpolyposis colorectal cancer (HNPCC). B's physician, a health care professional with...
45 CFR 146.122 - Additional requirements prohibiting discrimination based on genetic information.
Code of Federal Regulations, 2014 CFR
2014-10-01
... individual has a genetic variant associated with hereditary nonpolyposis colorectal cancer is a genetic test... manifested with respect to A. Example 2. (i) Facts. Individual B has several family members with colon cancer... hereditary nonpolyposis colorectal cancer (HNPCC). B's physician, a health care professional with...
Planning additional drilling campaign using two-space genetic algorithm: A game theoretical approach
NASA Astrophysics Data System (ADS)
Kumral, Mustafa; Ozer, Umit
2013-03-01
Grade and tonnage are the most important technical uncertainties in mining ventures because of the use of estimations/simulations, which are mostly generated from drill data. Open pit mines are planned and designed on the basis of the blocks representing the entire orebody. Each block has different estimation/simulation variance reflecting uncertainty to some extent. The estimation/simulation realizations are submitted to mine production scheduling process. However, the use of a block model with varying estimation/simulation variances will lead to serious risk in the scheduling. In the medium of multiple simulations, the dispersion variances of blocks can be thought to regard technical uncertainties. However, the dispersion variance cannot handle uncertainty associated with varying estimation/simulation variances of blocks. This paper proposes an approach that generates the configuration of the best additional drilling campaign to generate more homogenous estimation/simulation variances of blocks. In other words, the objective is to find the best drilling configuration in such a way as to minimize grade uncertainty under budget constraint. Uncertainty measure of the optimization process in this paper is interpolation variance, which considers data locations and grades. The problem is expressed as a minmax problem, which focuses on finding the best worst-case performance i.e., minimizing interpolation variance of the block generating maximum interpolation variance. Since the optimization model requires computing the interpolation variances of blocks being simulated/estimated in each iteration, the problem cannot be solved by standard optimization tools. This motivates to use two-space genetic algorithm (GA) approach to solve the problem. The technique has two spaces: feasible drill hole configuration with minimization of interpolation variance and drill hole simulations with maximization of interpolation variance. Two-space interacts to find a minmax solution
The use of a covariate reduces experimental error in nutrient digestion studies in growing pigs
Technology Transfer Automated Retrieval System (TEKTRAN)
Covariance analysis limits error, the degree of nuisance variation, and overparameterizing factors to accurately measure treatment effects. Data dealing with growth, carcass composition, and genetics often utilize covariates in data analysis. In contrast, nutritional studies typically do not. The ob...
Technology Transfer Automated Retrieval System (TEKTRAN)
Objective: To determine the extent to which the risk for incident coronary heart disease (CHD) increases in relation to a genetic risk score (GRS) that additively integrates the influence of high-risk alleles in nine documented single nucleotide polymorphisms (SNPs) for CHD, and to examine whether t...
Covariant mutually unbiased bases
NASA Astrophysics Data System (ADS)
Carmeli, Claudio; Schultz, Jussi; Toigo, Alessandro
2016-06-01
The connection between maximal sets of mutually unbiased bases (MUBs) in a prime-power dimensional Hilbert space and finite phase-space geometries is well known. In this article, we classify MUBs according to their degree of covariance with respect to the natural symmetries of a finite phase-space, which are the group of its affine symplectic transformations. We prove that there exist maximal sets of MUBs that are covariant with respect to the full group only in odd prime-power dimensional spaces, and in this case, their equivalence class is actually unique. Despite this limitation, we show that in dimension 2r covariance can still be achieved by restricting to proper subgroups of the symplectic group, that constitute the finite analogues of the oscillator group. For these subgroups, we explicitly construct the unitary operators yielding the covariance.
Construction of Covariance Functions with Variable Length Fields
NASA Technical Reports Server (NTRS)
Gaspari, Gregory; Cohn, Stephen E.; Guo, Jing; Pawson, Steven
2005-01-01
This article focuses on construction, directly in physical space, of three-dimensional covariance functions parametrized by a tunable length field, and on an application of this theory to reproduce the Quasi-Biennial Oscillation (QBO) in the Goddard Earth Observing System, Version 4 (GEOS-4) data assimilation system. These Covariance models are referred to as multi-level or nonseparable, to associate them with the application where a multi-level covariance with a large troposphere to stratosphere length field gradient is used to reproduce the QBO from sparse radiosonde observations in the tropical lower stratosphere. The multi-level covariance functions extend well-known single level covariance functions depending only on a length scale. Generalizations of the first- and third-order autoregressive covariances in three dimensions are given, providing multi-level covariances with zero and three derivatives at zero separation, respectively. Multi-level piecewise rational covariances with two continuous derivatives at zero separation are also provided. Multi-level powerlaw covariances are constructed with continuous derivatives of all orders. Additional multi-level covariance functions are constructed using the Schur product of single and multi-level covariance functions. A multi-level powerlaw covariance used to reproduce the QBO in GEOS-4 is described along with details of the assimilation experiments. The new covariance model is shown to represent the vertical wind shear associated with the QBO much more effectively than in the baseline GEOS-4 system.
Forsberg, Simon K. G.; Andreatta, Matthew E.; Huang, Xin-Yuan; Danku, John; Salt, David E.; Carlborg, Örjan
2015-01-01
Genome-wide association (GWA) analyses have generally been used to detect individual loci contributing to the phenotypic diversity in a population by the effects of these loci on the trait mean. More rarely, loci have also been detected based on variance differences between genotypes. Several hypotheses have been proposed to explain the possible genetic mechanisms leading to such variance signals. However, little is known about what causes these signals, or whether this genetic variance-heterogeneity reflects mechanisms of importance in natural populations. Previously, we identified a variance-heterogeneity GWA (vGWA) signal for leaf molybdenum concentrations in Arabidopsis thaliana. Here, fine-mapping of this association reveals that the vGWA emerges from the effects of three independent genetic polymorphisms that all are in strong LD with the markers displaying the genetic variance-heterogeneity. By revealing the genetic architecture underlying this vGWA signal, we uncovered the molecular source of a significant amount of hidden additive genetic variation or “missing heritability”. Two of the three polymorphisms underlying the genetic variance-heterogeneity are promoter variants for Molybdate transporter 1 (MOT1), and the third a variant located ~25 kb downstream of this gene. A fourth independent association was also detected ~600 kb upstream of MOT1. Use of a T-DNA knockout allele highlights Copper Transporter 6; COPT6 (AT2G26975) as a strong candidate gene for this association. Our results show that an extended LD across a complex locus including multiple functional alleles can lead to a variance-heterogeneity between genotypes in natural populations. Further, they provide novel insights into the genetic regulation of ion homeostasis in A. thaliana, and empirically confirm that variance-heterogeneity based GWA methods are a valuable tool to detect novel associations of biological importance in natural populations. PMID:26599497
Kumar, Satish; Molloy, Claire; Muñoz, Patricio; Daetwyler, Hans; Chagné, David; Volz, Richard
2015-01-01
The nonadditive genetic effects may have an important contribution to total genetic variation of phenotypes, so estimates of both the additive and nonadditive effects are desirable for breeding and selection purposes. Our main objectives were to: estimate additive, dominance and epistatic variances of apple (Malus × domestica Borkh.) phenotypes using relationship matrices constructed from genome-wide dense single nucleotide polymorphism (SNP) markers; and compare the accuracy of genomic predictions using genomic best linear unbiased prediction models with or without including nonadditive genetic effects. A set of 247 clonally replicated individuals was assessed for six fruit quality traits at two sites, and also genotyped using an Illumina 8K SNP array. Across several fruit quality traits, the additive, dominance, and epistatic effects contributed about 30%, 16%, and 19%, respectively, to the total phenotypic variance. Models ignoring nonadditive components yielded upwardly biased estimates of additive variance (heritability) for all traits in this study. The accuracy of genomic predicted genetic values (GEGV) varied from about 0.15 to 0.35 for various traits, and these were almost identical for models with or without including nonadditive effects. However, models including nonadditive genetic effects further reduced the bias of GEGV. Between-site genotypic correlations were high (>0.85) for all traits, and genotype-site interaction accounted for <10% of the phenotypic variability. The accuracy of prediction, when the validation set was present only at one site, was generally similar for both sites, and varied from about 0.50 to 0.85. The prediction accuracies were strongly influenced by trait heritability, and genetic relatedness between the training and validation families. PMID:26497141
NASA Astrophysics Data System (ADS)
Frasinski, Leszek J.
2016-08-01
Recent technological advances in the generation of intense femtosecond pulses have made covariance mapping an attractive analytical technique. The laser pulses available are so intense that often thousands of ionisation and Coulomb explosion events will occur within each pulse. To understand the physics of these processes the photoelectrons and photoions need to be correlated, and covariance mapping is well suited for operating at the high counting rates of these laser sources. Partial covariance is particularly useful in experiments with x-ray free electron lasers, because it is capable of suppressing pulse fluctuation effects. A variety of covariance mapping methods is described: simple, partial (single- and multi-parameter), sliced, contingent and multi-dimensional. The relationship to coincidence techniques is discussed. Covariance mapping has been used in many areas of science and technology: inner-shell excitation and Auger decay, multiphoton and multielectron ionisation, time-of-flight and angle-resolved spectrometry, infrared spectroscopy, nuclear magnetic resonance imaging, stimulated Raman scattering, directional gamma ray sensing, welding diagnostics and brain connectivity studies (connectomics). This review gives practical advice for implementing the technique and interpreting the results, including its limitations and instrumental constraints. It also summarises recent theoretical studies, highlights unsolved problems and outlines a personal view on the most promising research directions.
Misunderstanding analysis of covariance.
Miller, G A; Chapman, J P
2001-02-01
Despite numerous technical treatments in many venues, analysis of covariance (ANCOVA) remains a widely misused approach to dealing with substantive group differences on potential covariates, particularly in psychopathology research. Published articles reach unfounded conclusions, and some statistics texts neglect the issue. The problem with ANCOVA in such cases is reviewed. In many cases, there is no means of achieving the superficially appealing goal of "correcting" or "controlling for" real group differences on a potential covariate. In hopes of curtailing misuse of ANCOVA and promoting appropriate use, a nontechnical discussion is provided, emphasizing a substantive confound rarely articulated in textbooks and other general presentations, to complement the mathematical critiques already available. Some alternatives are discussed for contexts in which ANCOVA is inappropriate or questionable. PMID:11261398
Mulligan, Megan K.; DuBose, Candice; Yue, Junming; Miles, Michael F.; Lu, Lu; Hamre, Kristin M.
2013-01-01
The role of miRNA and miRNA biogenesis genes in the adult brain is just beginning to be explored. In this study we have performed a comprehensive analysis of the expression, genetic regulation, and co-expression of major components of the miRNA biogenesis pathway using human and mouse data sets and resources available on the GeneNetwork web site (genenetwork.org). We found a wide range of variation in expression in both species for key components of the pathway—Drosha, Pasha, and Dicer. Across species, tissues, and expression platforms all three genes are generally well-correlated. No single genetic locus exerts a strong and consistent influence on the expression of these key genes across murine brain regions. However, in mouse striatum, many members of the miRNA pathway are correlated—including Dicer, Drosha, Pasha, Ars2 (Srrt), Eif2c1 (Ago1), Eif2c2 (Ago2), Zcchc11, and Snip1. The expression of these genes may be partly influenced by a locus on Chromosome 9 (105.67–106.32 Mb). We explored ~1500 brain phenotypes available for the C57BL/6J × DBA/2J (BXD) genetic mouse population in order to identify miRNA biogenesis genes correlated with traits related to addiction and psychiatric disorders. We found a significant association between expression of Dicer and Drosha in several brain regions and the response to many drugs of abuse, including ethanol, cocaine, and methamphetamine. Expression of Dicer, Drosha, and Pasha in most of the brain regions explored is strongly correlated with the expression of key members of the dopamine system. Drosha, Pasha, and Dicer expression is also correlated with the expression of behavioral traits measuring depression and sensorimotor gating, impulsivity, and anxiety, respectively. Our study provides a global survey of the expression and regulation of key miRNA biogenesis genes in brain and provides preliminary support for the involvement of these genes and their product miRNAs in addiction and psychiatric disease processes
NASA Astrophysics Data System (ADS)
Bourget, Antoine; Troost, Jan
2016-03-01
We construct a covariant generating function for the spectrum of chiral primaries of symmetric orbifold conformal field theories with N = (4 , 4) supersymmetry in two dimensions. For seed target spaces K3 and T 4, the generating functions capture the SO(21) and SO(5) representation theoretic content of the chiral ring respectively. Via string dualities, we relate the transformation properties of the chiral ring under these isometries of the moduli space to the Lorentz covariance of perturbative string partition functions in flat space.
Evolutionary quantitative genetics of nonlinear developmental systems.
Morrissey, Michael B
2015-08-01
In quantitative genetics, the effects of developmental relationships among traits on microevolution are generally represented by the contribution of pleiotropy to additive genetic covariances. Pleiotropic additive genetic covariances arise only from the average effects of alleles on multiple traits, and therefore the evolutionary importance of nonlinearities in development is generally neglected in quantitative genetic views on evolution. However, nonlinearities in relationships among traits at the level of whole organisms are undeniably important to biology in general, and therefore critical to understanding evolution. I outline a system for characterizing key quantitative parameters in nonlinear developmental systems, which yields expressions for quantities such as trait means and phenotypic and genetic covariance matrices. I then develop a system for quantitative prediction of evolution in nonlinear developmental systems. I apply the system to generating a new hypothesis for why direct stabilizing selection is rarely observed. Other uses will include separation of purely correlative from direct and indirect causal effects in studying mechanisms of selection, generation of predictions of medium-term evolutionary trajectories rather than immediate predictions of evolutionary change over single generation time-steps, and the development of efficient and biologically motivated models for separating additive from epistatic genetic variances and covariances. PMID:26174586
Brazzola, Gregory; Chèvre, Nathalie; Wedekind, Claus
2014-01-01
The evolutionary potential of natural populations to adapt to anthropogenic threats critically depends on whether there exists additive genetic variation for tolerance to the threat. A major problem for water-dwelling organisms is chemical pollution, and among the most common pollutants is 17α-ethinylestradiol (EE2), the synthetic estrogen that is used in oral contraceptives and that can affect fish at various developmental stages, including embryogenesis. We tested whether there is variation in the tolerance to EE2 within Alpine whitefish. We sampled spawners from two species of different lakes, bred them in vitro in a full-factorial design each, and studied growth and mortality of embryos. Exposure to EE2 turned out to be toxic in all concentrations we tested (≥1 ng/L). It reduced embryo viability and slowed down embryogenesis. We found significant additive genetic variation in EE2-induced mortality in both species, that is, genotypes differed in their tolerance to estrogen pollution. We also found maternal effects on embryo development to be influenced by EE2, that is, some maternal sib groups were more susceptible to EE2 than others. In conclusion, the toxic effects of EE2 were strong, but both species demonstrated the kind of additive genetic variation that is necessary for an evolutionary response to this type of pollution. PMID:25553069
Brazzola, Gregory; Chèvre, Nathalie; Wedekind, Claus
2014-11-01
The evolutionary potential of natural populations to adapt to anthropogenic threats critically depends on whether there exists additive genetic variation for tolerance to the threat. A major problem for water-dwelling organisms is chemical pollution, and among the most common pollutants is 17α-ethinylestradiol (EE2), the synthetic estrogen that is used in oral contraceptives and that can affect fish at various developmental stages, including embryogenesis. We tested whether there is variation in the tolerance to EE2 within Alpine whitefish. We sampled spawners from two species of different lakes, bred them in vitro in a full-factorial design each, and studied growth and mortality of embryos. Exposure to EE2 turned out to be toxic in all concentrations we tested (≥1 ng/L). It reduced embryo viability and slowed down embryogenesis. We found significant additive genetic variation in EE2-induced mortality in both species, that is, genotypes differed in their tolerance to estrogen pollution. We also found maternal effects on embryo development to be influenced by EE2, that is, some maternal sib groups were more susceptible to EE2 than others. In conclusion, the toxic effects of EE2 were strong, but both species demonstrated the kind of additive genetic variation that is necessary for an evolutionary response to this type of pollution. PMID:25553069
Generalized Linear Covariance Analysis
NASA Technical Reports Server (NTRS)
Carpenter, James R.; Markley, F. Landis
2014-01-01
This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.
Generalized Linear Covariance Analysis
NASA Technical Reports Server (NTRS)
Carpenter, J. Russell; Markley, F. Landis
2008-01-01
We review and extend in two directions the results of prior work on generalized covariance analysis methods. This prior work allowed for partitioning of the state space into "solve-for" and "consider" parameters, allowed for differences between the formal values and the true values of the measurement noise, process noise, and a priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and a priori solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator s anchor time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the "variance sandpile" and the "sensitivity mosaic," and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.
Sequential BART for imputation of missing covariates.
Xu, Dandan; Daniels, Michael J; Winterstein, Almut G
2016-07-01
To conduct comparative effectiveness research using electronic health records (EHR), many covariates are typically needed to adjust for selection and confounding biases. Unfortunately, it is typical to have missingness in these covariates. Just using cases with complete covariates will result in considerable efficiency losses and likely bias. Here, we consider the covariates missing at random with missing data mechanism either depending on the response or not. Standard methods for multiple imputation can either fail to capture nonlinear relationships or suffer from the incompatibility and uncongeniality issues. We explore a flexible Bayesian nonparametric approach to impute the missing covariates, which involves factoring the joint distribution of the covariates with missingness into a set of sequential conditionals and applying Bayesian additive regression trees to model each of these univariate conditionals. Using data augmentation, the posterior for each conditional can be sampled simultaneously. We provide details on the computational algorithm and make comparisons to other methods, including parametric sequential imputation and two versions of multiple imputation by chained equations. We illustrate the proposed approach on EHR data from an affiliated tertiary care institution to examine factors related to hyperglycemia. PMID:26980459
Covariate analysis of bivariate survival data
Bennett, L.E.
1992-01-01
The methods developed are used to analyze the effects of covariates on bivariate survival data when censoring and ties are present. The proposed method provides models for bivariate survival data that include differential covariate effects and censored observations. The proposed models are based on an extension of the univariate Buckley-James estimators which replace censored data points by their expected values, conditional on the censoring time and the covariates. For the bivariate situation, it is necessary to determine the expectation of the failure times for one component conditional on the failure or censoring time of the other component. Two different methods have been developed to estimate these expectations. In the semiparametric approach these expectations are determined from a modification of Burke's estimate of the bivariate empirical survival function. In the parametric approach censored data points are also replaced by their conditional expected values where the expected values are determined from a specified parametric distribution. The model estimation will be based on the revised data set, comprised of uncensored components and expected values for the censored components. The variance-covariance matrix for the estimated covariate parameters has also been derived for both the semiparametric and parametric methods. Data from the Demographic and Health Survey was analyzed by these methods. The two outcome variables are post-partum amenorrhea and breastfeeding; education and parity were used as the covariates. Both the covariate parameter estimates and the variance-covariance estimates for the semiparametric and parametric models will be compared. In addition, a multivariate test statistic was used in the semiparametric model to examine contrasts. The significance of the statistic was determined from a bootstrap distribution of the test statistic.
Using Analysis of Covariance (ANCOVA) with Fallible Covariates
ERIC Educational Resources Information Center
Culpepper, Steven Andrew; Aguinis, Herman
2011-01-01
Analysis of covariance (ANCOVA) is used widely in psychological research implementing nonexperimental designs. However, when covariates are fallible (i.e., measured with error), which is the norm, researchers must choose from among 3 inadequate courses of action: (a) know that the assumption that covariates are perfectly reliable is violated but…
Gautam, Mayank; Dang, Yanwei; Ge, Xianhong; Shao, Yujiao; Li, Zaiyun
2016-01-01
Allopolyploidization with the merger of the genomes from different species has been shown to be associated with genetic and epigenetic changes. But the maintenance of such alterations related to one parental species after the genome is extracted from the allopolyploid remains to be detected. In this study, the genome of Brassica napus L. (2n = 38, genomes AACC) was extracted from its intergeneric allohexaploid (2n = 62, genomes AACCOO) with another crucifer Orychophragmus violaceus (2n = 24, genome OO), by backcrossing and development of alien addition lines. B. napus-type plants identified in the self-pollinated progenies of nine monosomic additions were analyzed by the methods of amplified fragment length polymorphism, sequence-specific amplified polymorphism, and methylation-sensitive amplified polymorphism. They showed modifications to certain extents in genomic components (loss and gain of DNA segments and transposons, introgression of alien DNA segments) and DNA methylation, compared with B. napus donor. The significant differences in the changes between the B. napus types extracted from these additions likely resulted from the different effects of individual alien chromosomes. Particularly, the additions which harbored the O. violaceus chromosome carrying dominant rRNA genes over those of B. napus tended to result in the development of plants which showed fewer changes, suggesting a role of the expression levels of alien rRNA genes in genomic stability. These results provided new cues for the genetic alterations in one parental genome that are maintained even after the genome becomes independent. PMID:27148282
Gautam, Mayank; Dang, Yanwei; Ge, Xianhong; Shao, Yujiao; Li, Zaiyun
2016-01-01
Allopolyploidization with the merger of the genomes from different species has been shown to be associated with genetic and epigenetic changes. But the maintenance of such alterations related to one parental species after the genome is extracted from the allopolyploid remains to be detected. In this study, the genome of Brassica napus L. (2n = 38, genomes AACC) was extracted from its intergeneric allohexaploid (2n = 62, genomes AACCOO) with another crucifer Orychophragmus violaceus (2n = 24, genome OO), by backcrossing and development of alien addition lines. B. napus-type plants identified in the self-pollinated progenies of nine monosomic additions were analyzed by the methods of amplified fragment length polymorphism, sequence-specific amplified polymorphism, and methylation-sensitive amplified polymorphism. They showed modifications to certain extents in genomic components (loss and gain of DNA segments and transposons, introgression of alien DNA segments) and DNA methylation, compared with B. napus donor. The significant differences in the changes between the B. napus types extracted from these additions likely resulted from the different effects of individual alien chromosomes. Particularly, the additions which harbored the O. violaceus chromosome carrying dominant rRNA genes over those of B. napus tended to result in the development of plants which showed fewer changes, suggesting a role of the expression levels of alien rRNA genes in genomic stability. These results provided new cues for the genetic alterations in one parental genome that are maintained even after the genome becomes independent. PMID:27148282
Parrella, Giuseppe; Acanfora, Nadia; Orílio, Anelise F; Navas-Castillo, Jesús
2011-06-01
Alfalfa mosaic virus (AMV) is a plant virus that is distributed worldwide and can induce necrosis and/or yellow mosaic on a large variety of plant species, including commercially important crops. It is the only virus of the genus Alfamovirus in the family Bromoviridae. AMV isolates can be clustered into two genetic groups that correlate with their geographic origin. Here, we report for the first time the complete nucleotide sequence of a Spanish isolate of AMV found infecting Cape honeysuckle (Tecoma capensis) and named Tec-1. The tripartite genome of Tec-1 is composed of 3643 nucleotides (nt) for RNA1, 2594 nt for RNA2 and 2037 nt for RNA3. Comparative sequence analysis of the coat protein gene revealed that the isolate Tec-1 is distantly related to subgroup I of AMV and more closely related to subgroup II, although forming a distinct phylogenetic clade. Therefore, we propose to split subgroup II of AMV into two subgroups, namely IIA, comprising isolates previously included in subgroup II, and IIB, including the novel Spanish isolate Tec-1. PMID:21327783
Colón-Llavina, Marlene M; Mignucci-Giannoni, Antonio A; Mattiucci, Simonetta; Paoletti, Michela; Nascetti, Giuseppe; Williams, Ernest H
2009-10-01
Studies of marine mammal parasites in the Caribbean are scarce. An assessment for marine mammal endo- and ectoparasites from Puerto Rico and the Virgin Islands, but extending to other areas of the Caribbean, was conducted between 1989 and 1994. The present study complements the latter and enhances identification of anisakid nematodes using molecular markers. Parasites were collected from 59 carcasses of stranded cetaceans and manatees from 1994 to 2006, including Globicephala macrorhynchus, Kogia breviceps, Kogia sima, Lagenodelphis hosei, Mesoplodon densirostris, Peponocephala electra, Stenella longirostris, Steno bredanensis, Trichechus manatus. Tursiops truncatus, and Ziphius cavirostris. Sixteen species of endoparasitic helminthes were morphologically identified, including two species of acanthocephalans (Bolbosoma capitatum, Bolbosoma vasculosum), nine species of nematodes (Anisakis sp., Anisakis brevispiculata, Anisakis paggiae, Anisakis simplex, Anisakis typica, Anisakis ziphidarium, Crassicauda anthonyi, Heterocheilus tunicatus, Pseudoterranova ceticola), two species of cestodes (Monorygma grimaldi, Phyllobothrium delphini), and three species of trematodes (Chiorchis groschafti, Pulmonicola cochleotrema, Monoligerum blairi). The nematodes belonging to the genus Anisakis recovered in some stranded animals were genetically identified to species level based on their sequence analysis of mitochondrial DNA (629 bp of mtDNA cox 2). A total of five new host records and six new geographic records are presented. PMID:19582477
Covariant approximation averaging
NASA Astrophysics Data System (ADS)
Shintani, Eigo; Arthur, Rudy; Blum, Thomas; Izubuchi, Taku; Jung, Chulwoo; Lehner, Christoph
2015-06-01
We present a new class of statistical error reduction techniques for Monte Carlo simulations. Using covariant symmetries, we show that correlation functions can be constructed from inexpensive approximations without introducing any systematic bias in the final result. We introduce a new class of covariant approximation averaging techniques, known as all-mode averaging (AMA), in which the approximation takes account of contributions of all eigenmodes through the inverse of the Dirac operator computed from the conjugate gradient method with a relaxed stopping condition. In this paper we compare the performance and computational cost of our new method with traditional methods using correlation functions and masses of the pion, nucleon, and vector meson in Nf=2 +1 lattice QCD using domain-wall fermions. This comparison indicates that AMA significantly reduces statistical errors in Monte Carlo calculations over conventional methods for the same cost.
Schwabe, Inga; Boomsma, Dorret I; Zeeuw, Eveline L de; Berg, Stéphanie M van den
2016-07-01
The often-used ACE model which decomposes phenotypic variance into additive genetic (A), common-environmental (C) and unique-environmental (E) parts can be extended to include covariates. Collection of these variables however often leads to a large amount of missing data, for example when self-reports (e.g. questionnaires) are not fully completed. The usual approach to handle missing covariate data in twin research results in reduced power to detect statistical effects, as only phenotypic and covariate data of individual twins with complete data can be used. Here we present a full information approach to handle missing covariate data that makes it possible to use all available data. A simulation study shows that, independent of missingness scenario, number of covariates or amount of missingness, the full information approach is more powerful than the usual approach. To illustrate the new method, we applied it to test scores on a Dutch national school achievement test (Eindtoets Basisonderwijs) in the final grade of primary school of 990 twin pairs. The effects of school-aggregated measures (e.g. school denomination, pedagogical philosophy, school size) and the effect of the sex of a twin on these test scores were tested. None of the covariates had a significant effect on individual differences in test scores. PMID:26687147
Covariant deformed oscillator algebras
NASA Technical Reports Server (NTRS)
Quesne, Christiane
1995-01-01
The general form and associativity conditions of deformed oscillator algebras are reviewed. It is shown how the latter can be fulfilled in terms of a solution of the Yang-Baxter equation when this solution has three distinct eigenvalues and satisfies a Birman-Wenzl-Murakami condition. As an example, an SU(sub q)(n) x SU(sub q)(m)-covariant q-bosonic algebra is discussed in some detail.
Partial covariate adjusted regression
Şentürk, Damla; Nguyen, Danh V.
2008-01-01
Covariate adjusted regression (CAR) is a recently proposed adjustment method for regression analysis where both the response and predictors are not directly observed (Şentürk and Müller, 2005). The available data has been distorted by unknown functions of an observable confounding covariate. CAR provides consistent estimators for the coefficients of the regression between the variables of interest, adjusted for the confounder. We develop a broader class of partial covariate adjusted regression (PCAR) models to accommodate both distorted and undistorted (adjusted/unadjusted) predictors. The PCAR model allows for unadjusted predictors, such as age, gender and demographic variables, which are common in the analysis of biomedical and epidemiological data. The available estimation and inference procedures for CAR are shown to be invalid for the proposed PCAR model. We propose new estimators and develop new inference tools for the more general PCAR setting. In particular, we establish the asymptotic normality of the proposed estimators and propose consistent estimators of their asymptotic variances. Finite sample properties of the proposed estimators are investigated using simulation studies and the method is also illustrated with a Pima Indians diabetes data set. PMID:20126296
Khondker, Zakaria S; Zhu, Hongtu; Chu, Haitao; Lin, Weili; Ibrahim, Joseph G.
2012-01-01
Estimation of sparse covariance matrices and their inverse subject to positive definiteness constraints has drawn a lot of attention in recent years. The abundance of high-dimensional data, where the sample size (n) is less than the dimension (d), requires shrinkage estimation methods since the maximum likelihood estimator is not positive definite in this case. Furthermore, when n is larger than d but not sufficiently larger, shrinkage estimation is more stable than maximum likelihood as it reduces the condition number of the precision matrix. Frequentist methods have utilized penalized likelihood methods, whereas Bayesian approaches rely on matrix decompositions or Wishart priors for shrinkage. In this paper we propose a new method, called the Bayesian Covariance Lasso (BCLASSO), for the shrinkage estimation of a precision (covariance) matrix. We consider a class of priors for the precision matrix that leads to the popular frequentist penalties as special cases, develop a Bayes estimator for the precision matrix, and propose an efficient sampling scheme that does not precalculate boundaries for positive definiteness. The proposed method is permutation invariant and performs shrinkage and estimation simultaneously for non-full rank data. Simulations show that the proposed BCLASSO performs similarly as frequentist methods for non-full rank data. PMID:24551316
Impact of the 235U Covariance Data in Benchmark Calculations
Leal, Luiz C; Mueller, Don; Arbanas, Goran; Wiarda, Dorothea; Derrien, Herve
2008-01-01
The error estimation for calculated quantities relies on nuclear data uncertainty information available in the basic nuclear data libraries such as the U.S. Evaluated Nuclear Data File (ENDF/B). The uncertainty files (covariance matrices) in the ENDF/B library are generally obtained from analysis of experimental data. In the resonance region, the computer code SAMMY is used for analyses of experimental data and generation of resonance parameters. In addition to resonance parameters evaluation, SAMMY also generates resonance parameter covariance matrices (RPCM). SAMMY uses the generalized least-squares formalism (Bayes method) together with the resonance formalism (R-matrix theory) for analysis of experimental data. Two approaches are available for creation of resonance-parameter covariance data. (1) During the data-evaluation process, SAMMY generates both a set of resonance parameters that fit the experimental data and the associated resonance-parameter covariance matrix. (2) For existing resonance-parameter evaluations for which no resonance-parameter covariance data are available, SAMMY can retroactively create a resonance-parameter covariance matrix. The retroactive method was used to generate covariance data for 235U. The resulting 235U covariance matrix was then used as input to the PUFF-IV code, which processed the covariance data into multigroup form, and to the TSUNAMI code, which calculated the uncertainty in the multiplication factor due to uncertainty in the experimental cross sections. The objective of this work is to demonstrate the use of the 235U covariance data in calculations of critical benchmark systems.
Earth Observing System Covariance Realism
NASA Technical Reports Server (NTRS)
Zaidi, Waqar H.; Hejduk, Matthew D.
2016-01-01
The purpose of covariance realism is to properly size a primary object's covariance in order to add validity to the calculation of the probability of collision. The covariance realism technique in this paper consists of three parts: collection/calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics. An empirical cumulative distribution function (ECDF) Goodness-of-Fit (GOF) method is employed to determine if a covariance is properly sized by comparing the empirical distribution of Mahalanobis distance calculations to the hypothesized parent 3-DoF chi-squared distribution. To realistically size a covariance for collision probability calculations, this study uses a state noise compensation algorithm that adds process noise to the definitive epoch covariance to account for uncertainty in the force model. Process noise is added until the GOF tests pass a group significance level threshold. The results of this study indicate that when outliers attributed to persistently high or extreme levels of solar activity are removed, the aforementioned covariance realism compensation method produces a tuned covariance with up to 80 to 90% of the covariance propagation timespan passing (against a 60% minimum passing threshold) the GOF tests-a quite satisfactory and useful result.
Covariant magnetic connection hypersurfaces
NASA Astrophysics Data System (ADS)
Pegoraro, F.
2016-04-01
> In the single fluid, non-relativistic, ideal magnetohydrodynamic (MHD) plasma description, magnetic field lines play a fundamental role by defining dynamically preserved `magnetic connections' between plasma elements. Here we show how the concept of magnetic connection needs to be generalized in the case of a relativistic MHD description where we require covariance under arbitrary Lorentz transformations. This is performed by defining 2-D magnetic connection hypersurfaces in the 4-D Minkowski space. This generalization accounts for the loss of simultaneity between spatially separated events in different frames and is expected to provide a powerful insight into the 4-D geometry of electromagnetic fields when .
Gamal El-Dien, Omnia; Ratcliffe, Blaise; Klápště, Jaroslav; Porth, Ilga; Chen, Charles; El-Kassaby, Yousry A.
2016-01-01
The open-pollinated (OP) family testing combines the simplest known progeny evaluation and quantitative genetics analyses as candidates’ offspring are assumed to represent independent half-sib families. The accuracy of genetic parameter estimates is often questioned as the assumption of “half-sibling” in OP families may often be violated. We compared the pedigree- vs. marker-based genetic models by analysing 22-yr height and 30-yr wood density for 214 white spruce [Picea glauca (Moench) Voss] OP families represented by 1694 individuals growing on one site in Quebec, Canada. Assuming half-sibling, the pedigree-based model was limited to estimating the additive genetic variances which, in turn, were grossly overestimated as they were confounded by very minor dominance and major additive-by-additive epistatic genetic variances. In contrast, the implemented genomic pairwise realized relationship models allowed the disentanglement of additive from all nonadditive factors through genetic variance decomposition. The marker-based models produced more realistic narrow-sense heritability estimates and, for the first time, allowed estimating the dominance and epistatic genetic variances from OP testing. In addition, the genomic models showed better prediction accuracies compared to pedigree models and were able to predict individual breeding values for new individuals from untested families, which was not possible using the pedigree-based model. Clearly, the use of marker-based relationship approach is effective in estimating the quantitative genetic parameters of complex traits even under simple and shallow pedigree structure. PMID:26801647
Homozygous; Inheritance; Heterozygous; Inheritance patterns; Heredity and disease; Heritable; Genetic markers ... The chromosomes are made up of strands of genetic information called DNA. Each chromosome contains sections of ...
... Inheritance; Heterozygous; Inheritance patterns; Heredity and disease; Heritable; Genetic markers ... The chromosomes are made up of strands of genetic information called DNA. Each chromosome contains sections of ...
Waldmann, Patrik; Hallander, Jon; Hoti, Fabian; Sillanpää, Mikko J.
2008-01-01
Accurate and fast computation of quantitative genetic variance parameters is of great importance in both natural and breeding populations. For experimental designs with complex relationship structures it can be important to include both additive and dominance variance components in the statistical model. In this study, we introduce a Bayesian Gibbs sampling approach for estimation of additive and dominance genetic variances in the traditional infinitesimal model. The method can handle general pedigrees without inbreeding. To optimize between computational time and good mixing of the Markov chain Monte Carlo (MCMC) chains, we used a hybrid Gibbs sampler that combines a single site and a blocked Gibbs sampler. The speed of the hybrid sampler and the mixing of the single-site sampler were further improved by the use of pretransformed variables. Two traits (height and trunk diameter) from a previously published diallel progeny test of Scots pine (Pinus sylvestris L.) and two large simulated data sets with different levels of dominance variance were analyzed. We also performed Bayesian model comparison on the basis of the posterior predictive loss approach. Results showed that models with both additive and dominance components had the best fit for both height and diameter and for the simulated data with high dominance. For the simulated data with low dominance, we needed an informative prior to avoid the dominance variance component becoming overestimated. The narrow-sense heritability estimates in the Scots pine data were lower compared to the earlier results, which is not surprising because the level of dominance variance was rather high, especially for diameter. In general, the hybrid sampler was considerably faster than the blocked sampler and displayed better mixing properties than the single-site sampler. PMID:18558655
Waldmann, Patrik; Hallander, Jon; Hoti, Fabian; Sillanpää, Mikko J
2008-06-01
Accurate and fast computation of quantitative genetic variance parameters is of great importance in both natural and breeding populations. For experimental designs with complex relationship structures it can be important to include both additive and dominance variance components in the statistical model. In this study, we introduce a Bayesian Gibbs sampling approach for estimation of additive and dominance genetic variances in the traditional infinitesimal model. The method can handle general pedigrees without inbreeding. To optimize between computational time and good mixing of the Markov chain Monte Carlo (MCMC) chains, we used a hybrid Gibbs sampler that combines a single site and a blocked Gibbs sampler. The speed of the hybrid sampler and the mixing of the single-site sampler were further improved by the use of pretransformed variables. Two traits (height and trunk diameter) from a previously published diallel progeny test of Scots pine (Pinus sylvestris L.) and two large simulated data sets with different levels of dominance variance were analyzed. We also performed Bayesian model comparison on the basis of the posterior predictive loss approach. Results showed that models with both additive and dominance components had the best fit for both height and diameter and for the simulated data with high dominance. For the simulated data with low dominance, we needed an informative prior to avoid the dominance variance component becoming overestimated. The narrow-sense heritability estimates in the Scots pine data were lower compared to the earlier results, which is not surprising because the level of dominance variance was rather high, especially for diameter. In general, the hybrid sampler was considerably faster than the blocked sampler and displayed better mixing properties than the single-site sampler. PMID:18558655
Covariance-enhanced discriminant analysis
XU, PEIRONG; ZHU, JI; ZHU, LIXING; LI, YI
2016-01-01
Summary Linear discriminant analysis has been widely used to characterize or separate multiple classes via linear combinations of features. However, the high dimensionality of features from modern biological experiments defies traditional discriminant analysis techniques. Possible interfeature correlations present additional challenges and are often underused in modelling. In this paper, by incorporating possible interfeature correlations, we propose a covariance-enhanced discriminant analysis method that simultaneously and consistently selects informative features and identifies the corresponding discriminable classes. Under mild regularity conditions, we show that the method can achieve consistent parameter estimation and model selection, and can attain an asymptotically optimal misclassification rate. Extensive simulations have verified the utility of the method, which we apply to a renal transplantation trial.
Hoffmann, A.A.; Parsons, P.A. )
1989-08-01
Previously we found that Drosophila melanogaster lines selected for increased desiccation resistance have lowered metabolic rate and behavioral activity levels, and show correlated responses for resistance to starvation and a toxic ethanol level. These results were consistent with a prediction that increased resistance to many environmental stresses may be genetically correlated because of a reduction in metabolic energy expenditure. Here we present experiments on the genetic basis of the selection response and extend the study of correlated responses to other stresses. The response to selection was not sex-specific and involved X-linked and autosomal genes acting additively. Activity differences contributed little to differences in desiccation resistance between selected and control lines. Selected lines had lower metabolic rates than controls in darkness when activity was inhibited. Adults from selected lines showed increased resistance to a heat shock, {sup 60}Co-gamma-radiation, and acute ethanol and acetic acid stress. The desiccation, ethanol and starvation resistance of isofemale lines set up from the F2s of a cross between one of the selected and one of the control lines were correlated. Selected and control lines did not differ in ether-extractable lipid content or in resistance to acetone, ether or a cold shock.
Grimm, Alexander; Rasenack, Maria; Athanasopoulou, Ioanna M; Dammeier, Nele Maria; Lipski, Christina; Wolking, Stefan; Vittore, Debora; Décard, Bernhard F; Axer, Hubertus
2016-02-01
The objective of this study is to evaluate the nerve ultrasound characteristics in genetically distinct inherited neuropathies, the value of the modified ultrasound pattern sum score (mUPSS) to differentiate between the subtypes and the correlation of ultrasound with nerve conduction studies (NCS), disease duration and severity. All patients underwent a standardized neurological examination, ultrasound, and NCS. In addition, genetic testing was performed. Consequently, mUPSS was applied, which is a sum-score of cross-sectional areas (CSA) at predefined anatomical points in different nerves. 31 patients were included (10xCharcot-Marie-Tooth (CMT)1a, 3xCMT1b, 3xCMTX, 9xCMT2, 6xHNPP [Hereditary neuropathy with liability to pressure palsies]). Generalized, homogeneous nerve enlargement and significantly increased UPS scores emphasized the diagnosis of demyelinating neuropathy, particularly CMT1a and CMT1b. The amount of enlargement did not depend on disease duration, symptom severity, height and weight. In CMTX the nerves were enlarged, as well, however, only in the roots and lower limbs, most prominent in men. In CMT2 no significant enlargement was detectable. In HNPP the CSA values were increased at entrapped sites, and not elsewhere. However, a distinction from CMT1, which also showed enlarged CSA values at entrapment sites, was only possible by calculating the entrapment ratios and entrapment score. The mUPSS allowed distinction between CMT1a (increased UPS scores, entrapment ratios <1.0) and HNPP (low UPS scores, entrapment ratios >1.4), while CMT1b and CMTX showed intermediate UPS types and entrapment ratios <1.0. Although based on few cases, ultrasound revealed consistent and homogeneous nerve alteration in certain inherited neuropathies. The modified UPSS is a quantitative tool, which may provide useful information for diagnosis, differentiation and follow-up evaluation in addition to NCS and molecular testing. PMID:26559821
Stardust Navigation Covariance Analysis
NASA Astrophysics Data System (ADS)
Menon, Premkumar R.
2000-01-01
The Stardust spacecraft was launched on February 7, 1999 aboard a Boeing Delta-II rocket. Mission participants include the National Aeronautics and Space Administration (NASA), the Jet Propulsion Laboratory (JPL), Lockheed Martin Astronautics (LMA) and the University of Washington. The primary objective of the mission is to collect in-situ samples of the coma of comet Wild-2 and return those samples to the Earth for analysis. Mission design and operational navigation for Stardust is performed by the Jet Propulsion Laboratory (JPL). This paper will describe the extensive JPL effort in support of the Stardust pre-launch analysis of the orbit determination component of the mission covariance study. A description of the mission and it's trajectory will be provided first, followed by a discussion of the covariance procedure and models. Predicted accuracy's will be examined as they relate to navigation delivery requirements for specific critical events during the mission. Stardust was launched into a heliocentric trajectory in early 1999. It will perform an Earth Gravity Assist (EGA) on January 15, 2001 to acquire an orbit for the eventual rendezvous with comet Wild-2. The spacecraft will fly through the coma (atmosphere) on the dayside of Wild-2 on January 2, 2004. At that time samples will be obtained using an aerogel collector. After the comet encounter Stardust will return to Earth when the Sample Return Capsule (SRC) will separate and land at the Utah Test Site (UTTR) on January 15, 2006. The spacecraft will however be deflected off into a heliocentric orbit. The mission is divided into three phases for the covariance analysis. They are 1) Launch to EGA, 2) EGA to Wild-2 encounter and 3) Wild-2 encounter to Earth reentry. Orbit determination assumptions for each phase are provided. These include estimated and consider parameters and their associated a-priori uncertainties. Major perturbations to the trajectory include 19 deterministic and statistical maneuvers
Application of covariant analytic mechanics to gravity with Dirac field
NASA Astrophysics Data System (ADS)
Nakajima, Satoshi
2016-03-01
We applied the covariant analytic mechanics with the differential forms to the Dirac field and the gravity with the Dirac field. The covariant analytic mechanics treats space and time on an equal footing regarding the differential forms as the basis variables. A significant feature of the covariant analytic mechanics is that the canonical equations, in addition to the Euler-Lagrange equation, are not only manifestly general coordinate covariant but also gauge covariant. Combining our study and the previous works (the scalar field, the abelian and non-abelian gauge fields and the gravity without the Dirac field), the applicability of the covariant analytic mechanics was checked for all fundamental fields. We studied both the first and second order formalism of the gravitational field coupled with matters including the Dirac field. It was suggested that gravitation theories including higher order curvatures cannot be treated by the second order formalism in the covariant analytic mechanics. In addition, we showed that the covariant analytic mechanics is equivalent to corrected De Donder-Weyl theory.
The incredible shrinking covariance estimator
NASA Astrophysics Data System (ADS)
Theiler, James
2012-05-01
Covariance estimation is a key step in many target detection algorithms. To distinguish target from background requires that the background be well-characterized. This applies to targets ranging from the precisely known chemical signatures of gaseous plumes to the wholly unspecified signals that are sought by anomaly detectors. When the background is modelled by a (global or local) Gaussian or other elliptically contoured distribution (such as Laplacian or multivariate-t), a covariance matrix must be estimated. The standard sample covariance overfits the data, and when the training sample size is small, the target detection performance suffers. Shrinkage addresses the problem of overfitting that inevitably arises when a high-dimensional model is fit from a small dataset. In place of the (overfit) sample covariance matrix, a linear combination of that covariance with a fixed matrix is employed. The fixed matrix might be the identity, the diagonal elements of the sample covariance, or some other underfit estimator. The idea is that the combination of an overfit with an underfit estimator can lead to a well-fit estimator. The coefficient that does this combining, called the shrinkage parameter, is generally estimated by some kind of cross-validation approach, but direct cross-validation can be computationally expensive. This paper extends an approach suggested by Hoffbeck and Landgrebe, and presents efficient approximations of the leave-one-out cross-validation (LOOC) estimate of the shrinkage parameter used in estimating the covariance matrix from a limited sample of data.
Hallin, Sara; Throbäck, Ingela Noredal; Dicksved, Johan; Pell, Mikael
2006-01-01
External carbon sources can enhance denitrification rates and thus improve nitrogen removal in wastewater treatment plants. The effects of adding methanol and ethanol on the genetic and metabolic diversity of denitrifying communities in activated sludge were compared using a pilot-scale plant with two parallel lines. A full-scale plant receiving the same municipal wastewater, but without external carbon source addition, was the reference. Metabolic profiles obtained from potential denitrification rates with 10 electron donors showed that the denitrifying communities altered their preferences for certain compounds after supplementation with methanol or ethanol and that methanol had the greater impact. Clone libraries of nirK and nirS genes, encoding the two different nitrite reductases in denitrifiers, revealed that methanol also increased the diversity of denitrifiers of the nirS type, which indicates that denitrifiers favored by methanol were on the rise in the community. This suggests that there might be a niche differentiation between nirS and nirK genotypes during activated sludge processes. The composition of nirS genotypes also varied greatly among all samples, whereas the nirK communities were more stable. The latter was confirmed by denaturing gradient gel electrophoresis of nirK communities on all sampling occasions. Our results support earlier hypotheses that the compositions of denitrifier communities change during predenitrification processes when external carbon sources are added, although no severe effect could be observed from an operational point of view. PMID:16885297
Covariant Electrodynamics in Vacuum
NASA Astrophysics Data System (ADS)
Wilhelm, H. E.
1990-05-01
The generalized Galilei covariant Maxwell equations and their EM field transformations are applied to the vacuum electrodynamics of a charged particle moving with an arbitrary velocity v in an inertial frame with EM carrier (ether) of velocity w. In accordance with the Galilean relativity principle, all velocities have absolute meaning (relative to the ether frame with isotropic light propagation), and the relative velocity of two bodies is defined by the linear relation uG = v1 - v2. It is shown that the electric equipotential surfaces of a charged particle are compressed in the direction parallel to its relative velocity v - w (mechanism for physical length contraction of bodies). The magnetic field H(r, t) excited in the ether by a charge e moving uniformly with velocity v is related to its electric field E(r, t) by the equation H=ɛ0(v - w)xE/[ 1 +w • (t>- w)/c20], which shows that (i) a magnetic field is excited only if the charge moves relative to the ether, and (ii) the magnetic field is weak if v - w is not comparable to the velocity of light c0 . It is remarkable that a charged particle can excite EM shock waves in the ether if |i> - w > c0. This condition is realizable for anti-parallel charge and ether velocities if |v-w| > c0- | w|, i.e., even if |v| is subluminal. The possibility of this Cerenkov effect in the ether is discussed for terrestrial and galactic situations
Halfhill, M D; Millwood, R J; Weissinger, A K; Warwick, S I; Stewart, C N
2003-11-01
The level of transgene expression in crop x weed hybrids and the degree to which crop-specific genes are integrated into hybrid populations are important factors in assessing the potential ecological and agricultural risks of gene flow associated with genetic engineering. The average transgene zygosity and genetic structure of transgenic hybrid populations change with the progression of generations, and the green fluorescent protein (GFP) transgene is an ideal marker to quantify transgene expression in advancing populations. The homozygous T(1) single-locus insert GFP/ Bacillus thuringiensis (Bt) transgenic canola ( Brassica napus, cv Westar) with two copies of the transgene fluoresced twice as much as hemizygous individuals with only one copy of the transgene. These data indicate that the expression of the GFP gene was additive, and fluorescence could be used to determine zygosity status. Several hybrid generations (BC(1)F(1), BC(2)F(1)) were produced by backcrossing various GFP/Bt transgenic canola ( B. napus, cv Westar) and birdseed rape ( Brassica rapa) hybrid generations onto B. rapa. Intercrossed generations (BC(2)F(2) Bulk) were generated by crossing BC(2)F(1) individuals in the presence of a pollinating insect ( Musca domestica L.). The ploidy of plants in the BC(2)F(2) Bulk hybrid generation was identical to the weedy parental species, B. rapa. AFLP analysis was used to quantify the degree of B. napus introgression into multiple backcross hybrid generations with B. rapa. The F(1) hybrid generations contained 95-97% of the B. napus-specific AFLP markers, and each successive backcross generation demonstrated a reduction of markers resulting in the 15-29% presence in the BC(2)F(2) Bulk population. Average fluorescence of each successive hybrid generation was analyzed, and homozygous canola lines and hybrid populations that contained individuals homozygous for GFP (BC(2)F(2) Bulk) demonstrated significantly higher fluorescence than hemizygous hybrid
Bayesian recursive mixed linear model for gene expression analyses with continuous covariates.
Casellas, J; Ibáñez-Escriche, N
2012-01-01
The analysis of microarray gene expression data has experienced a remarkable growth in scientific research over the last few years and is helping to decipher the genetic background of several productive traits. Nevertheless, most analytical approaches have relied on the comparison of 2 (or a few) well-defined groups of biological conditions where the continuous covariates have no sense (e.g., healthy vs. cancerous cells). Continuous effects could be of special interest when analyzing gene expression in animal production-oriented studies (e.g., birth weight), although very few studies address this peculiarity in the animal science framework. Within this context, we have developed a recursive linear mixed model where not only are linear covariates accounted for during gene expression analyses but also hierarchized and the effects of their genetic, environmental, and residual components on differential gene expression inferred independently. This parameterization allows a step forward in the inference of differential gene expression linked to a given quantitative trait such as birth weight. The statistical performance of this recursive model was exemplified under simulation by accounting for different sample sizes (n), heritabilities for the quantitative trait (h(2)), and magnitudes of differential gene expression (λ). It is important to highlight that statistical power increased with n, h(2), and λ, and the recursive model exceeded the standard linear mixed model with linear (nonrecursive) covariates in the majority of scenarios. This new parameterization would provide new insights about gene expression in the animal science framework, opening a new research scenario where within-covariate sources of differential gene expression could be individualized and estimated. The source code of the program accommodating these analytical developments and additional information about practical aspects on running the program are freely available by request to the corresponding
Palmer, Rohan H C; Nugent, Nicole R; Brick, Leslie A; Bidwell, Cinnamon L; McGeary, John E; Keller, Matthew C; Knopik, Valerie S
2016-06-01
Exposure to traumatic experiences is associated with an increased risk for drug dependence and poorer response to substance abuse treatment (Claus & Kindleberger, 2002; Jaycox, Ebener, Damesek, & Becker, 2004). Despite this evidence, the reasons for the observed associations of trauma and the general tendency to be dependent upon drugs of abuse remain unclear. Data (N = 2,596) from the Study of Addiction: Genetics and Environment were used to analyze (a) the degree to which commonly occurring single nucleotide polymorphisms (SNPs; minor allele frequency > 1%) in the human genome explains exposure to interpersonal traumatic experiences, and (b) the extent to which additive genetic effects on trauma are shared with additive genetic effects on drug dependence. Our results suggested moderate additive genetic influences on interpersonal trauma, h(2) SNP-Interpersonal = .47, 95% confidence interval (CI) [.10, .85], that are partially shared with additive genetic effects on generalized vulnerability to drug dependence, h(2) SNP-DD = .36, 95% CI [.11, .61]; rG-SNP = .49, 95% CI [.02, .96]. Although the design/technique does not exclude the possibility that substance abuse causally increases risk for traumatic experiences (or vice versa), these findings raise the possibility that commonly occurring SNPs influence both the general tendency towards drug dependence and interpersonal trauma. PMID:27214850
Covariant Closed String Coherent States
Hindmarsh, Mark; Skliros, Dimitri
2011-02-25
We give the first construction of covariant coherent closed string states, which may be identified with fundamental cosmic strings. We outline the requirements for a string state to describe a cosmic string, and provide an explicit and simple map that relates three different descriptions: classical strings, light cone gauge quantum states, and covariant vertex operators. The resulting coherent state vertex operators have a classical interpretation and are in one-to-one correspondence with arbitrary classical closed string loops.
Covariant closed string coherent states.
Hindmarsh, Mark; Skliros, Dimitri
2011-02-25
We give the first construction of covariant coherent closed string states, which may be identified with fundamental cosmic strings. We outline the requirements for a string state to describe a cosmic string, and provide an explicit and simple map that relates three different descriptions: classical strings, light cone gauge quantum states, and covariant vertex operators. The resulting coherent state vertex operators have a classical interpretation and are in one-to-one correspondence with arbitrary classical closed string loops. PMID:21405564
LISREL Modeling: Genetic and Environmental Influences on IQ Revisited.
ERIC Educational Resources Information Center
Chipuer, Heather M.; And Others
1990-01-01
A model-fitting analysis of the covariance structure of an intelligence quotient (IQ) data set is reported using a model that considers additive and nonadditive genetic parameters and shared and nonshared environment parameters that permit different estimates for different types of relatives. The use of LISREL for such purposes is reviewed. (SLD)
Holmans, Peter; Moskvina, Valentina; Jones, Lesley; Sharma, Manu; Vedernikov, Alexey; Buchel, Finja; Sadd, Mohamad; Bras, Jose M.; Bettella, Francesco; Nicolaou, Nayia; Simón-Sánchez, Javier; Mittag, Florian; Gibbs, J. Raphael; Schulte, Claudia; Durr, Alexandra; Guerreiro, Rita; Hernandez, Dena; Brice, Alexis; Stefánsson, Hreinn; Majamaa, Kari; Gasser, Thomas; Heutink, Peter; Wood, Nicholas W.; Martinez, Maria; Singleton, Andrew B.; Nalls, Michael A.; Hardy, John; Morris, Huw R.; Williams, Nigel M.; Arepalli, Sampath; Barker, Roger; Barrett, Jeffrey; Ben-Shlomo, Yoav; Berendse, Henk W.; Berg, Daniela; Bhatia, Kailash; de Bie, Rob M.A.; Biffi, Alessandro; Bloem, Bas; Brice, Alexis; Bochdanovits, Zoltan; Bonin, Michael; Bras, Jose M.; Brockmann, Kathrin; Brooks, Janet; Burn, David J.; Charlesworth, Gavin; Chen, Honglei; Chinnery, Patrick F.; Chong, Sean; Clarke, Carl E.; Cookson, Mark R.; Cooper, Jonathan M.; Corvol, Jen-Christophe; Counsell, Carl; Damier, Philippe; Dartigues, Jean Francois; Deloukas, Panagiotis; Deuschl, Günther; Dexter, David T.; van Dijk, Karin D.; Dillman, Allissa; Durif, Frank; Durr, Alexandra; Edkins, Sarah; Evans, Jonathan R.; Foltynie, Thomas; Gao, Jianjun; Gardner, Michelle; Gasser, Thomas; Gibbs, J. Raphael; Goate, Alison; Gray, Emma; Guerreiro, Rita; Gústafsson, Ómar; Hardy, John; Harris, Clare; Hernandez, Dena G.; Heutink, Peter; van Hilten, Jacobus J.; Hofman, Albert; Hollenbeck, Albert; Holmans, Peter; Holton, Janice; Hu, Michele; Huber, Heiko; Hudson, Gavin; Hunt, Sarah E.; Huttenlocher, Johanna; Illig, Thomas; Langford, Cordelia; Lees, Andrew; Lesage, Suzanne; Lichtner, Peter; Limousin, Patricia; Lopez, Grisel; Lorenz, Delia; Martinez, Maria; McNeill, Alisdair; Moorby, Catriona; Moore, Matthew; Morris, Huw; Morrison, Karen E.; Moskvina, Valentina; Mudanohwo, Ese; Nalls, Michael A.; Pearson, Justin; Perlmutter, Joel S.; Pétursson, Hjörvar; Plagnol, Vincent; Pollak, Pierre; Post, Bart; Potter, Simon; Ravina, Bernard; Revesz, Tamas; Riess, Olaf; Rivadeneira, Fernando; Rizzu, Patrizia; Ryten, Mina; Saad, Mohamad; Sawcer, Stephen; Schapira, Anthony; Scheffer, Hans; Sharma, Manu; Shaw, Karen; Sheerin, Una-Marie; Shoulson, Ira; Schulte, Claudia; Sidransky, Ellen; Simón-Sánchez, Javier; Singleton, Andrew B.; Smith, Colin; Stefánsson, Hreinn; Stefánsson, Kári; Steinberg, Stacy; Stockton, Joanna D.; Sveinbjornsdottir, Sigurlaug; Talbot, Kevin; Tanner, Carlie M.; Tashakkori-Ghanbaria, Avazeh; Tison, François; Trabzuni, Daniah; Traynor, Bryan J.; Uitterlinden, André G.; Velseboer, Daan; Vidailhet, Marie; Walker, Robert; van de Warrenburg, Bart; Wickremaratchi, Mirdhu; Williams, Nigel; Williams-Gray, Caroline H.; Winder-Rhodes, Sophie; Wood, Nicholas
2013-01-01
Parkinson's disease (PD) is the second most common neurodegenerative disease affecting 1–2% in people >60 and 3–4% in people >80. Genome-wide association (GWA) studies have now implicated significant evidence for association in at least 18 genomic regions. We have studied a large PD-meta analysis and identified a significant excess of SNPs (P < 1 × 10−16) that are associated with PD but fall short of the genome-wide significance threshold. This result was independent of variants at the 18 previously implicated regions and implies the presence of additional polygenic risk alleles. To understand how these loci increase risk of PD, we applied a pathway-based analysis, testing for biological functions that were significantly enriched for genes containing variants associated with PD. Analysing two independent GWA studies, we identified that both had a significant excess in the number of functional categories enriched for PD-associated genes (minimum P = 0.014 and P = 0.006, respectively). Moreover, 58 categories were significantly enriched for associated genes in both GWA studies (P < 0.001), implicating genes involved in the ‘regulation of leucocyte/lymphocyte activity’ and also ‘cytokine-mediated signalling’ as conferring an increased susceptibility to PD. These results were unaltered by the exclusion of all 178 genes that were present at the 18 genomic regions previously reported to be strongly associated with PD (including the HLA locus). Our findings, therefore, provide independent support to the strong association signal at the HLA locus and imply that the immune-related genetic susceptibility to PD is likely to be more widespread in the genome than previously appreciated. PMID:23223016
David, Sean P.; Strong, David R.; Leventhal, Adam M.; Lancaster, Molly A.; McGeary, John E.; Munafò, Marcus R.; Bergen, Andrew W.; Swan, Gary E.; Benowitz, Neal L.; Tyndale, Rachel F.; Conti, David V.; Brown, Richard A.; Lerman, Caryn; Niaura, Raymond
2013-01-01
Aims To evaluate associations of treatment and an ‘additive genetic efficacy score’ (AGES) based on dopamine functional polymorphisms with time to first smoking lapse and point prevalence abstinence at end of treatment among participants enrolled in two randomized clinical trials of smoking cessation therapies. Design Double-blind pharmacogenetic efficacy trials randomizing participants to active or placebo bupropion. Study 1 also randomized participants to cognitive-behavioral smoking cessation treatment (CBT) or this treatment with CBT for depression. Study 2 provided standardized behavioural support. Setting Two Hospital-affiliated clinics (Study 1), and two University-affiliated clinics (Study 2). Participants N=792 self-identified white treatment-seeking smokers aged ≥18 years smoking ≥10 cigarettes per day over the last year. Measurements Age, gender, Fagerström Test for Nicotine Dependence, dopamine pathway genotypes (rs1800497 [ANKK1 E713K], rs4680 [COMT V158M], DRD4 exon 3 Variable Number of Tandem Repeats polymorphism [DRD4 VNTR], SLC6A3 3' VNTR) analyzed both separately and as part of an AGES, time to first lapse, and point prevalence abstinence at end of treatment. Findings Significant associations of the AGES (hazard ratio = 1.10, 95% Confidence Interval [CI] = 1.06–1.14], p=0.0099) and of the DRD4 VNTR (HR = 1.29, 95%CI 1.17–1.41, p=0.0073) were observed with time to first lapse. A significant AGES by pharmacotherapy interaction was observed (β [SE]=−0.18 [0.07], p=0.016), such that AGES predicted risk for time to first lapse only for individuals randomized to placebo. Conclusions A score based on functional polymorphisms relating to dopamine pathways appears to predict lapse to smoking following a quit attempt, and the association is mitigated in smokers using bupropion. PMID:23941313
Welch, Allison M; Smith, Michael J; Gerhardt, H Carl
2014-06-01
Genetic variation in sexual displays is crucial for an evolutionary response to sexual selection, but can be eroded by strong selection. Identifying the magnitude and sources of additive genetic variance underlying sexually selected traits is thus an important issue in evolutionary biology. We conducted a quantitative genetics experiment with gray treefrogs (Hyla versicolor) to investigate genetic variances and covariances among features of the male advertisement call. Two energetically expensive traits showed significant genetic variation: call duration, expressed as number of pulses per call, and call rate, represented by its inverse, call period. These two properties also showed significant genetic covariance, consistent with an energetic constraint to call production. Combining the genetic variance-covariance matrix with previous estimates of directional sexual selection imposed by female preferences predicts a limited increase in call duration but no change in call rate despite significant selection on both traits. In addition to constraints imposed by the genetic covariance structure, an evolutionary response to sexual selection may also be limited by high energetic costs of long-duration calls and by preferences that act most strongly against very short-duration calls. Meanwhile, the persistence of these preferences could be explained by costs of mating with males with especially unattractive calls. PMID:24621402
RNA sequence analysis using covariance models.
Eddy, S R; Durbin, R
1994-01-01
We describe a general approach to several RNA sequence analysis problems using probabilistic models that flexibly describe the secondary structure and primary sequence consensus of an RNA sequence family. We call these models 'covariance models'. A covariance model of tRNA sequences is an extremely sensitive and discriminative tool for searching for additional tRNAs and tRNA-related sequences in sequence databases. A model can be built automatically from an existing sequence alignment. We also describe an algorithm for learning a model and hence a consensus secondary structure from initially unaligned example sequences and no prior structural information. Models trained on unaligned tRNA examples correctly predict tRNA secondary structure and produce high-quality multiple alignments. The approach may be applied to any family of small RNA sequences. Images PMID:8029015
Shrinkage estimators for covariance matrices.
Daniels, M J; Kass, R E
2001-12-01
Estimation of covariance matrices in small samples has been studied by many authors. Standard estimators, like the unstructured maximum likelihood estimator (ML) or restricted maximum likelihood (REML) estimator, can be very unstable with the smallest estimated eigenvalues being too small and the largest too big. A standard approach to more stably estimating the matrix in small samples is to compute the ML or REML estimator under some simple structure that involves estimation of fewer parameters, such as compound symmetry or independence. However, these estimators will not be consistent unless the hypothesized structure is correct. If interest focuses on estimation of regression coefficients with correlated (or longitudinal) data, a sandwich estimator of the covariance matrix may be used to provide standard errors for the estimated coefficients that are robust in the sense that they remain consistent under misspecification of the covariance structure. With large matrices, however, the inefficiency of the sandwich estimator becomes worrisome. We consider here two general shrinkage approaches to estimating the covariance matrix and regression coefficients. The first involves shrinking the eigenvalues of the unstructured ML or REML estimator. The second involves shrinking an unstructured estimator toward a structured estimator. For both cases, the data determine the amount of shrinkage. These estimators are consistent and give consistent and asymptotically efficient estimates for regression coefficients. Simulations show the improved operating characteristics of the shrinkage estimators of the covariance matrix and the regression coefficients in finite samples. The final estimator chosen includes a combination of both shrinkage approaches, i.e., shrinking the eigenvalues and then shrinking toward structure. We illustrate our approach on a sleep EEG study that requires estimation of a 24 x 24 covariance matrix and for which inferences on mean parameters critically
Blankers, T; Lübke, A K; Hennig, R M
2015-09-01
Studying the genetic architecture of sexual traits provides insight into the rate and direction at which traits can respond to selection. Traits associated with few loci and limited genetic and phenotypic constraints tend to evolve at high rates typically observed for secondary sexual characters. Here, we examined the genetic architecture of song traits and female song preferences in the field crickets Gryllus rubens and Gryllus texensis. Song and preference data were collected from both species and interspecific F1 and F2 hybrids. We first analysed phenotypic variation to examine interspecific differentiation and trait distributions in parental and hybrid generations. Then, the relative contribution of additive and additive-dominance variation was estimated. Finally, phenotypic variance-covariance (P) matrices were estimated to evaluate the multivariate phenotype available for selection. Song traits and preferences had unimodal trait distributions, and hybrid offspring were intermediate with respect to the parents. We uncovered additive and dominance variation in song traits and preferences. For two song traits, we found evidence for X-linked inheritance. On the one hand, the observed genetic architecture does not suggest rapid divergence, although sex linkage may have allowed for somewhat higher evolutionary rates. On the other hand, P matrices revealed that multivariate variation in song traits aligned with major dimensions in song preferences, suggesting a strong selection response. We also found strong covariance between the main traits that are sexually selected and traits that are not directly selected by females, providing an explanation for the striking multivariate divergence in male calling songs despite limited divergence in female preferences. PMID:26134540
Technology Transfer Automated Retrieval System (TEKTRAN)
An additive genetic risk score (GRS) for coronary heart disease (CHD) has previously been associated with incident CHD in the population-based Greek European Prospective Investigation into Cancer and nutrition (EPIC) cohort. In this study, we explore GRS-‘environment’ joint actions on CHD for severa...
Impact of nonrandom mating on genetic variance and gene flow in populations with mass selection.
Sánchez, Leopoldo; Woolliams, John A
2004-01-01
The mechanisms by which nonrandom mating affects selected populations are not completely understood and remain a subject of scientific debate in the development of tractable predictors of population characteristics. The main objective of this study was to provide a predictive model for the genetic variance and covariance among mates for traits subjected to directional selection in populations with nonrandom mating based on the pedigree. Stochastic simulations were used to check the validity of this model. Our predictions indicate that the positive covariance among mates that is expected to result with preferential mating of relatives can be severely overpredicted from neutral expectations. The covariance expected from neutral theory is offset by an opposing covariance between the genetic mean of an individual's family and the Mendelian sampling term of its mate. This mechanism was able to predict the reduction in covariance among mates that we observed in the simulated populations and, in consequence, the equilibrium genetic variance and expected long-term genetic contributions. Additionally, this study provided confirmatory evidence on the postulated relationships of long-term genetic contributions with both the rate of genetic gain and the rate of inbreeding (deltaF) with nonrandom mating. The coefficient of variation of the expected gene flow among individuals and deltaF was sensitive to nonrandom mating when heritability was low, but less so as heritability increased, and the theory developed in the study was sufficient to explain this phenomenon. PMID:15020441
Covariance expressions for eigenvalue and eigenvector problems
NASA Astrophysics Data System (ADS)
Liounis, Andrew J.
There are a number of important scientific and engineering problems whose solutions take the form of an eigenvalue--eigenvector problem. Some notable examples include solutions to linear systems of ordinary differential equations, controllability of linear systems, finite element analysis, chemical kinetics, fitting ellipses to noisy data, and optimal estimation of attitude from unit vectors. In many of these problems, having knowledge of the eigenvalue and eigenvector Jacobians is either necessary or is nearly as important as having the solution itself. For instance, Jacobians are necessary to find the uncertainty in a computed eigenvalue or eigenvector estimate. This uncertainty, which is usually represented as a covariance matrix, has been well studied for problems similar to the eigenvalue and eigenvector problem, such as singular value decomposition. There has been substantially less research on the covariance of an optimal estimate originating from an eigenvalue-eigenvector problem. In this thesis we develop two general expressions for the Jacobians of eigenvalues and eigenvectors with respect to the elements of their parent matrix. The expressions developed make use of only the parent matrix and the eigenvalue and eigenvector pair under consideration. In addition, they are applicable to any general matrix (including complex valued matrices, eigenvalues, and eigenvectors) as long as the eigenvalues are simple. Alongside this, we develop expressions that determine the uncertainty in a vector estimate obtained from an eigenvalue-eigenvector problem given the uncertainty of the terms of the matrix. The Jacobian expressions developed are numerically validated with forward finite, differencing and the covariance expressions are validated using Monte Carlo analysis. Finally, the results from this work are used to determine covariance expressions for a variety of estimation problem examples and are also applied to the design of a dynamical system.
Kochunov, Peter; Jahanshad, Neda; Sprooten, Emma; Nichols, Thomas E.; Mandl, René C.; Almasy, Laura; Booth, Tom; Brouwer, Rachel M.; Curran, Joanne E.; de Zubicaray, Greig I.; Dimitrova, Rali; Duggirala, Ravi; Fox, Peter T.; Hong, L. Elliot; Landman, Bennett A.; Lemaitre, Hervé; Lopez, Lorna; Martin, Nicholas G.; McMahon, Katie L.; Mitchell, Braxton D.; Olvera, Rene L.; Peterson, Charles P.; Starr, John M.; Sussmann, Jessika E.; Toga, Arthur W.; Wardlaw, Joanna M.; Wright, Margaret J.; Wright, Susan N.; Bastin, Mark E.; McIntosh, Andrew M.; Boomsma, Dorret I.; Kahn, René S.; den Braber, Anouk; de Geus, Eco JC; Deary, Ian J.; Hulshoff Pol, Hilleke E.; Williamson, Douglas E.; Blangero, John; van ’t Ent, Dennis; Thompson, Paul M.; Glahn, David C.
2014-01-01
Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9–85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large “mega-family”. We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability. PMID:24657781
Kochunov, Peter; Jahanshad, Neda; Sprooten, Emma; Nichols, Thomas E; Mandl, René C; Almasy, Laura; Booth, Tom; Brouwer, Rachel M; Curran, Joanne E; de Zubicaray, Greig I; Dimitrova, Rali; Duggirala, Ravi; Fox, Peter T; Hong, L Elliot; Landman, Bennett A; Lemaitre, Hervé; Lopez, Lorna M; Martin, Nicholas G; McMahon, Katie L; Mitchell, Braxton D; Olvera, Rene L; Peterson, Charles P; Starr, John M; Sussmann, Jessika E; Toga, Arthur W; Wardlaw, Joanna M; Wright, Margaret J; Wright, Susan N; Bastin, Mark E; McIntosh, Andrew M; Boomsma, Dorret I; Kahn, René S; den Braber, Anouk; de Geus, Eco J C; Deary, Ian J; Hulshoff Pol, Hilleke E; Williamson, Douglas E; Blangero, John; van 't Ent, Dennis; Thompson, Paul M; Glahn, David C
2014-07-15
Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability. PMID:24657781
Progress of Covariance Evaluation at the China Nuclear Data Center
Xu, R.; Zhang, Q.; Zhang, Y.; Liu, T.; Ge, Z.; Lu, H.; Sun, Z.; Yu, B.; Tang, G.
2015-01-15
Covariance evaluations at the China Nuclear Data Center focus on the cross sections of structural materials and actinides in the fast neutron energy range. In addition to the well-known Least-squares approach, a method based on the analysis of the sources of experimental uncertainties is especially introduced to generate a covariance matrix for a particular reaction for which multiple measurements are available. The scheme of the covariance evaluation flow is presented, and an example of n+{sup 90}Zr is given to illuminate the whole procedure. It is proven that the accuracy of measurements can be properly incorporated into the covariance and the long-standing small uncertainty problem can be avoided.
Optimal Estimation and Rank Detection for Sparse Spiked Covariance Matrices
Cai, Tony; Ma, Zongming; Wu, Yihong
2014-01-01
This paper considers a sparse spiked covariancematrix model in the high-dimensional setting and studies the minimax estimation of the covariance matrix and the principal subspace as well as the minimax rank detection. The optimal rate of convergence for estimating the spiked covariance matrix under the spectral norm is established, which requires significantly different techniques from those for estimating other structured covariance matrices such as bandable or sparse covariance matrices. We also establish the minimax rate under the spectral norm for estimating the principal subspace, the primary object of interest in principal component analysis. In addition, the optimal rate for the rank detection boundary is obtained. This result also resolves the gap in a recent paper by Berthet and Rigollet [2] where the special case of rank one is considered. PMID:26257453
A class of covariate-dependent spatiotemporal covariance functions
Reich, Brian J; Eidsvik, Jo; Guindani, Michele; Nail, Amy J; Schmidt, Alexandra M.
2014-01-01
In geostatistics, it is common to model spatially distributed phenomena through an underlying stationary and isotropic spatial process. However, these assumptions are often untenable in practice because of the influence of local effects in the correlation structure. Therefore, it has been of prolonged interest in the literature to provide flexible and effective ways to model non-stationarity in the spatial effects. Arguably, due to the local nature of the problem, we might envision that the correlation structure would be highly dependent on local characteristics of the domain of study, namely the latitude, longitude and altitude of the observation sites, as well as other locally defined covariate information. In this work, we provide a flexible and computationally feasible way for allowing the correlation structure of the underlying processes to depend on local covariate information. We discuss the properties of the induced covariance functions and discuss methods to assess its dependence on local covariate information by means of a simulation study and the analysis of data observed at ozone-monitoring stations in the Southeast United States. PMID:24772199
Technology Transfer Automated Retrieval System (TEKTRAN)
The genus Capsicum represents one of several well characterized Solanaceous genera. A wealth of classical and molecular genetics research is available for the genus. Information gleaned from its cultivated relatives, tomato and potato, provide further insight for basic and applied studies. Early ...
Technology Transfer Automated Retrieval System (TEKTRAN)
Maintaining genetic variation in wild populations of Arctic organisms is fundamental to the long-term persistence of high latitude biodiversity. Variability is important because it provides options for species to respond to changing environmental conditions and novel challenges such as emerging path...
Covariant constraints in ghost free massive gravity
Deffayet, C.; Mourad, J.; Zahariade, G. E-mail: mourad@apc.univ-paris7.fr
2013-01-01
We show that the reformulation of the de Rham-Gabadadze-Tolley massive gravity theory using vielbeins leads to a very simple and covariant way to count constraints, and hence degrees of freedom. Our method singles out a subset of theories, in the de Rham-Gabadadze-Tolley family, where an extra constraint, needed to eliminate the Boulware Deser ghost, is easily seen to appear. As a side result, we also introduce a new method, different from the Stuckelberg trick, to extract kinetic terms for the polarizations propagating in addition to those of the massless graviton.
Are Eddy Covariance series stationary?
Technology Transfer Automated Retrieval System (TEKTRAN)
Spectral analysis via a discrete Fourier transform is used often to examine eddy covariance series for cycles (eddies) of interest. Generally the analysis is performed on hourly or half-hourly data sets collected at 10 or 20 Hz. Each original series is often assumed to be stationary. Also automated ...
Dabelea, D; Pettitt, D J
2001-01-01
Numerous studies have reported that offspring whose mothers had type 2 diabetes mellitus (DM) are more likely to develop type 2 DM, impaired glucose tolerance, and obesity at an early age than offspring whose fathers had DM. Exposure to the diabetic intrauterine environment has been shown to be an important risk factor for all these conditions. To what extent transmission of type 2 DM from mother to offspring is the effect of genetic inheritance and to what extent it is the long-term consequence of exposure to maternal hyperglycemia is still uncertain. There are, of course, interactions between the diabetic intrauterine environment and genetics. Several data in experimental animals as well as in humans suggest, however, that exposure of the fetus to the mother's DM confers a risk for type 2 DM and obesity that is above any genetically transmitted susceptibility. In the Pima Indian population much of the increase in childhood type 2 DM can be attributed to the diabetic intrauterine environment. This suggests that intensive glucose control during pregnancy might have extended beneficial effects, contributing to a decrease in the prevalence of childhood type 2 DM. PMID:11592564
AFCI-2.0 Neutron Cross Section Covariance Library
Herman, M.; Herman, M; Oblozinsky, P.; Mattoon, C.M.; Pigni, M.; Hoblit, S.; Mughabghab, S.F.; Sonzogni, A.; Talou, P.; Chadwick, M.B.; Hale, G.M.; Kahler, A.C.; Kawano, T.; Little, R.C.; Yount, P.G.
2011-03-01
materials and fission products, and 20 actinides. Covariances are given in 33-energy groups, from 10?5 eV to 19.6 MeV, obtained by processing with LANL processing code NJOY using 1/E flux. In addition to these 110 files, the library contains 20 files with nu-bar covariances, 3 files with covariances of prompt fission neutron spectra (238,239,240-Pu), and 2 files with mu-bar covariances (23-Na, 56-Fe). Over the period of three years several working versions of the library have been released and tested by ANL and INL reactor analysts. Useful feedback has been collected allowing gradual improvements of the library. In addition, QA system was developed to check basic properties and features of the whole library, allowing visual inspection of uncertainty and correlations plots, inspection of uncertainties of integral quantities with independent databases, and dispersion of cross sections between major evaluated libraries. The COMMARA-2.0 beta version of the library was released to ANL and INL reactor analysts in October 2010. The final version, described in the present report, was released in March 2011.
Summary of the Workshop on Neutron Cross Section Covariances
Smith, Donald L.
2008-12-15
A Workshop on Neutron Cross Section Covariances was held from June 24-27, 2008, in Port Jefferson, New York. This Workshop was organized by the National Nuclear Data Center, Brookhaven National Laboratory, to provide a forum for reporting on the status of the growing field of neutron cross section covariances for applications and for discussing future directions of the work in this field. The Workshop focused on the following four major topical areas: covariance methodology, recent covariance evaluations, covariance applications, and user perspectives. Attention was given to the entire spectrum of neutron cross section covariance concerns ranging from light nuclei to the actinides, and from the thermal energy region to 20 MeV. The papers presented at this conference explored topics ranging from fundamental nuclear physics concerns to very specific applications in advanced reactor design and nuclear criticality safety. This paper provides a summary of this workshop. Brief comments on the highlights of each Workshop contribution are provided. In addition, a perspective on the achievements and shortcomings of the Workshop as well as on the future direction of research in this field is offered.
Luhmann, Ulrich F.O.; Carvalho, Livia S.; Holthaus, Sophia-Martha kleine; Cowing, Jill A.; Greenaway, Simon; Chu, Colin J.; Herrmann, Philipp; Smith, Alexander J.; Munro, Peter M.G.; Potter, Paul; Bainbridge, James W.B.; Ali, Robin R.
2015-01-01
Understanding phenotype–genotype correlations in retinal degeneration is a major challenge. Mutations in CRB1 lead to a spectrum of autosomal recessive retinal dystrophies with variable phenotypes suggesting the influence of modifying factors. To establish the contribution of the genetic background to phenotypic variability associated with the Crb1rd8/rd8 mutation, we compared the retinal pathology of Crb1rd8/rd8/J inbred mice with that of two Crb1rd8/rd8 lines backcrossed with C57BL/6JOlaHsd mice. Topical endoscopic fundal imaging and scanning laser ophthalmoscopy fundus images of all three Crb1rd8/rd8 lines showed a significant increase in the number of inferior retinal lesions that was strikingly variable between the lines. Optical coherence tomography, semithin, ultrastructural morphology and assessment of inflammatory and vascular marker by immunohistochemistry and quantitative reverse transcriptase-polymerase chain reaction revealed that the lesions were associated with photoreceptor death, Müller and microglia activation and telangiectasia-like vascular remodelling—features that were stable in the inbred, variable in the second, but virtually absent in the third Crb1rd8/rd8 line, even at 12 months of age. This suggests that the Crb1rd8/rd8 mutation is necessary, but not sufficient for the development of these degenerative features. By whole-genome SNP analysis of the genotype–phenotype correlation, a candidate region on chromosome 15 was identified. This may carry one or more genetic modifiers for the manifestation of the retinal pathology associated with mutations in Crb1. This study also provides insight into the nature of the retinal vascular lesions that likely represent a clinical correlate for the formation of retinal telangiectasia or Coats-like vasculopathy in patients with CRB1 mutations that are thought to depend on such genetic modifiers. PMID:25147295
Luhmann, Ulrich F O; Carvalho, Livia S; Holthaus, Sophia-Martha Kleine; Cowing, Jill A; Greenaway, Simon; Chu, Colin J; Herrmann, Philipp; Smith, Alexander J; Munro, Peter M G; Potter, Paul; Bainbridge, James W B; Ali, Robin R
2015-01-01
Understanding phenotype-genotype correlations in retinal degeneration is a major challenge. Mutations in CRB1 lead to a spectrum of autosomal recessive retinal dystrophies with variable phenotypes suggesting the influence of modifying factors. To establish the contribution of the genetic background to phenotypic variability associated with the Crb1(rd8/rd8) mutation, we compared the retinal pathology of Crb1(rd8/rd8)/J inbred mice with that of two Crb1(rd8/rd8) lines backcrossed with C57BL/6JOlaHsd mice. Topical endoscopic fundal imaging and scanning laser ophthalmoscopy fundus images of all three Crb1(rd8/rd8) lines showed a significant increase in the number of inferior retinal lesions that was strikingly variable between the lines. Optical coherence tomography, semithin, ultrastructural morphology and assessment of inflammatory and vascular marker by immunohistochemistry and quantitative reverse transcriptase-polymerase chain reaction revealed that the lesions were associated with photoreceptor death, Müller and microglia activation and telangiectasia-like vascular remodelling-features that were stable in the inbred, variable in the second, but virtually absent in the third Crb1(rd8/rd8) line, even at 12 months of age. This suggests that the Crb1(rd8/rd8) mutation is necessary, but not sufficient for the development of these degenerative features. By whole-genome SNP analysis of the genotype-phenotype correlation, a candidate region on chromosome 15 was identified. This may carry one or more genetic modifiers for the manifestation of the retinal pathology associated with mutations in Crb1. This study also provides insight into the nature of the retinal vascular lesions that likely represent a clinical correlate for the formation of retinal telangiectasia or Coats-like vasculopathy in patients with CRB1 mutations that are thought to depend on such genetic modifiers. PMID:25147295
ERIC Educational Resources Information Center
Moeyaert, Mariola; Ugille, Maaike; Ferron, John M.; Beretvas, S. Natasha; Van den Noortgate, Wim
2016-01-01
The impact of misspecifying covariance matrices at the second and third levels of the three-level model is evaluated. Results indicate that ignoring existing covariance has no effect on the treatment effect estimate. In addition, the between-case variance estimates are unbiased when covariance is either modeled or ignored. If the research interest…
Minimal unitary (covariant) scattering theory
Lindesay, J.V.; Markevich, A.
1983-06-01
In the minimal three particle equations developed by Lindesay the two body input amplitude was an on shell relativistic generalization of the non-relativistic scattering model characterized by a single mass parameter ..mu.. which in the two body (m + m) system looks like an s-channel bound state (..mu.. < 2m) or virtual state (..mu.. > 2m). Using this driving term in covariant Faddeev equations generates a rich covariant and unitary three particle dynamics. However, the simplest way of writing the relativisitic generalization of the Faddeev equations can take the on shell Mandelstam parameter s = 4(q/sup 2/ + m/sup 2/), in terms of which the two particle input is expressed, to negative values in the range of integration required by the dynamics. This problem was met in the original treatment by multiplying the two particle input amplitude by THETA(s). This paper provides what we hope to be a more direct way of meeting the problem.
Covariant jump conditions in electromagnetism
NASA Astrophysics Data System (ADS)
Itin, Yakov
2012-02-01
A generally covariant four-dimensional representation of Maxwell's electrodynamics in a generic material medium can be achieved straightforwardly in the metric-free formulation of electromagnetism. In this setup, the electromagnetic phenomena are described by two tensor fields, which satisfy Maxwell's equations. A generic tensorial constitutive relation between these fields is an independent ingredient of the theory. By use of different constitutive relations (local and non-local, linear and non-linear, etc.), a wide area of applications can be covered. In the current paper, we present the jump conditions for the fields and for the energy-momentum tensor on an arbitrarily moving surface between two media. From the differential and integral Maxwell equations, we derive the covariant boundary conditions, which are independent of any metric and connection. These conditions include the covariantly defined surface current and are applicable to an arbitrarily moving smooth curved boundary surface. As an application of the presented jump formulas, we derive a Lorentzian type metric as a condition for existence of the wave front in isotropic media. This result holds for ordinary materials as well as for metamaterials with negative material constants.
A covariant Fokker-Planck equation for a simple gas from relativistic kinetic theory
Chacon-Acosta, Guillermo; Dagdug, Leonardo; Morales-Tecotl, Hugo A.
2010-12-14
A manifestly covariant Fokker-Planck differential equation is derived for the case of a relativistic simple gas by taking a small momentum transfer approximation within the collision integral of the relativistic Boltzmann equation. We follow closely previous work, with the main difference that we keep manifest covariance at every stage of the analysis. In addition, we use the covariant Juettner distribution function to find a relativistic generalization of the Einstein's fluctuation-dissipation relation.
Covariance Modifications to Subspace Bases
Harris, D B
2008-11-19
Adaptive signal processing algorithms that rely upon representations of signal and noise subspaces often require updates to those representations when new data become available. Subspace representations frequently are estimated from available data with singular value (SVD) decompositions. Subspace updates require modifications to these decompositions. Updates can be performed inexpensively provided they are low-rank. A substantial literature on SVD updates exists, frequently focusing on rank-1 updates (see e.g. [Karasalo, 1986; Comon and Golub, 1990, Badeau, 2004]). In these methods, data matrices are modified by addition or deletion of a row or column, or data covariance matrices are modified by addition of the outer product of a new vector. A recent paper by Brand [2006] provides a general and efficient method for arbitrary rank updates to an SVD. The purpose of this note is to describe a closely-related method for applications where right singular vectors are not required. This note also describes the SVD updates to a particular scenario of interest in seismic array signal processing. The particular application involve updating the wideband subspace representation used in seismic subspace detectors [Harris, 2006]. These subspace detectors generalize waveform correlation algorithms to detect signals that lie in a subspace of waveforms of dimension d {ge} 1. They potentially are of interest because they extend the range of waveform variation over which these sensitive detectors apply. Subspace detectors operate by projecting waveform data from a detection window into a subspace specified by a collection of orthonormal waveform basis vectors (referred to as the template). Subspace templates are constructed from a suite of normalized, aligned master event waveforms that may be acquired by a single sensor, a three-component sensor, an array of such sensors or a sensor network. The template design process entails constructing a data matrix whose columns contain the
Moreira, X; Zas, R; Sampedro, L
2013-01-01
The apparent failure of invasions by alien pines in Europe has been explained by the co-occurrence of native pine congeners supporting herbivores that might easily recognize the new plants as hosts. Previous studies have reported that exotic pines show reduced tolerance and capacity to induce resistance to those native herbivores. We hypothesize that limited genetic variation in resistance to native herbivores and the existence of evolutionary trade-offs between growth and resistance could represent additional potential constraints on the evolution of invasiveness of exotic pines outside their natural range. In this paper, we examined genetic variation for constitutive and induced chemical defences (measured as non-volatile resin in the stem and total phenolics in the needles) and resistance to two major native generalist herbivores of pines in cafeteria bioassays (the phloem-feeder Hylobius abietis and the defoliator Thaumetopoea pityocampa) using half-sib families drawn from a sample of the population of Pinus radiata introduced to Spain in the mid-19th century. We found (i) significant genetic variation, with moderate-to-high narrow-sense heritabilities for both the production of constitutive non-volatile resin and induced total phenolics, and for constitutive resistance against T. pityocampa in bioassays, (ii) no evolutionary trade-offs between plant resistance and growth traits or between the production of different quantitative chemical defences and (iii) a positive genetic correlation between constitutive resistance to the two studied herbivores. Overall, results of our study indicate that the exotic pine P. radiata has limited genetic constraints on the evolution of resistance against herbivores in its introduced range, suggesting that, at least in terms of interactions with these enemies, this pine species has potential to become invasive in the future. PMID:23232833
Moreira, X; Zas, R; Sampedro, L
2013-05-01
The apparent failure of invasions by alien pines in Europe has been explained by the co-occurrence of native pine congeners supporting herbivores that might easily recognize the new plants as hosts. Previous studies have reported that exotic pines show reduced tolerance and capacity to induce resistance to those native herbivores. We hypothesize that limited genetic variation in resistance to native herbivores and the existence of evolutionary trade-offs between growth and resistance could represent additional potential constraints on the evolution of invasiveness of exotic pines outside their natural range. In this paper, we examined genetic variation for constitutive and induced chemical defences (measured as non-volatile resin in the stem and total phenolics in the needles) and resistance to two major native generalist herbivores of pines in cafeteria bioassays (the phloem-feeder Hylobius abietis and the defoliator Thaumetopoea pityocampa) using half-sib families drawn from a sample of the population of Pinus radiata introduced to Spain in the mid-19th century. We found (i) significant genetic variation, with moderate-to-high narrow-sense heritabilities for both the production of constitutive non-volatile resin and induced total phenolics, and for constitutive resistance against T. pityocampa in bioassays, (ii) no evolutionary trade-offs between plant resistance and growth traits or between the production of different quantitative chemical defences and (iii) a positive genetic correlation between constitutive resistance to the two studied herbivores. Overall, results of our study indicate that the exotic pine P. radiata has limited genetic constraints on the evolution of resistance against herbivores in its introduced range, suggesting that, at least in terms of interactions with these enemies, this pine species has potential to become invasive in the future. PMID:23232833
Logistics for Working Together to Facilitate Genomic/Quantitative Genetic Prediction
Technology Transfer Automated Retrieval System (TEKTRAN)
The incorporation of DNA tests into the national cattle evaluation system will require estimation of variances of and covariances among the additive genetic components of the DNA tests and the phenotypic traits they are intended to predict. Populations with both DNA test results and phenotypes will ...
Connecting Math and Motion: A Covariational Approach
NASA Astrophysics Data System (ADS)
Culbertson, Robert J.; Thompson, A. S.
2006-12-01
We define covariational reasoning as the ability to correlate changes in two connected variables. For example, the ability to describe the height of fluid in an odd-shaped vessel as a function of fluid volume requires covariational reasoning skills. Covariational reasoning ability is an essential resource for gaining a deep understanding of the physics of motion. We have developed an approach for teaching physical science to in-service math and science high school teachers that emphasizes covariational reasoning. Several examples of covariation and results from a small cohort of local teachers will be presented.
Covariance Evaluation Methodology for Neutron Cross Sections
Herman,M.; Arcilla, R.; Mattoon, C.M.; Mughabghab, S.F.; Oblozinsky, P.; Pigni, M.; Pritychenko, b.; Songzoni, A.A.
2008-09-01
We present the NNDC-BNL methodology for estimating neutron cross section covariances in thermal, resolved resonance, unresolved resonance and fast neutron regions. The three key elements of the methodology are Atlas of Neutron Resonances, nuclear reaction code EMPIRE, and the Bayesian code implementing Kalman filter concept. The covariance data processing, visualization and distribution capabilities are integral components of the NNDC methodology. We illustrate its application on examples including relatively detailed evaluation of covariances for two individual nuclei and massive production of simple covariance estimates for 307 materials. Certain peculiarities regarding evaluation of covariances for resolved resonances and the consistency between resonance parameter uncertainties and thermal cross section uncertainties are also discussed.
The association between intelligence and lifespan is mostly genetic
Arden, Rosalind; Deary, Ian J; Reynolds, Chandra A; Pedersen, Nancy L; Plassman, Brenda L; McGue, Matt; Christensen, Kaare; Visscher, Peter M
2016-01-01
Background: Several studies in the new field of cognitive epidemiology have shown that higher intelligence predicts longer lifespan. This positive correlation might arise from socioeconomic status influencing both intelligence and health; intelligence leading to better health behaviours; and/or some shared genetic factors influencing both intelligence and health. Distinguishing among these hypotheses is crucial for medicine and public health, but can only be accomplished by studying a genetically informative sample. Methods: We analysed data from three genetically informative samples containing information on intelligence and mortality: Sample 1, 377 pairs of male veterans from the NAS-NRC US World War II Twin Registry; Sample 2, 246 pairs of twins from the Swedish Twin Registry; and Sample 3, 784 pairs of twins from the Danish Twin Registry. The age at which intelligence was measured differed between the samples. We used three methods of genetic analysis to examine the relationship between intelligence and lifespan: we calculated the proportion of the more intelligent twins who outlived their co-twin; we regressed within-twin-pair lifespan differences on within-twin-pair intelligence differences; and we used the resulting regression coefficients to model the additive genetic covariance. We conducted a meta-analysis of the regression coefficients across the three samples. Results: The combined (and all three individual samples) showed a small positive phenotypic correlation between intelligence and lifespan. In the combined sample observed r = .12 (95% confidence interval .06 to .18). The additive genetic covariance model supported a genetic relationship between intelligence and lifespan. In the combined sample the genetic contribution to the covariance was 95%; in the US study, 84%; in the Swedish study, 86%, and in the Danish study, 85%. Conclusions: The finding of common genetic effects between lifespan and intelligence has important implications for public
Connolly, Eric J; Beaver, Kevin M
2016-04-01
Emerging evidence from longitudinal research suggests that bullied children are more likely to develop antisocial tendencies and mental health problems later in life. Less research, however, has used genetically sensitive research designs to control for genetic confounding and examine whether the well-supported association between bullying victimization and maladaptive development is partially accounted for by common genetic and environmental influences. Using sibling data from the National Longitudinal Survey of Youth 1997, the current study used a series of bivariate liability-threshold models to disentangle the genetic and environmental influences on observed covariance between repeated bullying victimization, delinquent involvement, and symptoms of depression/anxiety. Results revealed that common additive genetic and nonshared environmental effects accounted for the covariance in liability between bullying victimization and delinquent involvement as well as bullying victimization and symptoms of depression/anxiety. The results suggest the presence of genotype-environment correlation (rGE) between repeated victimization and maladaptive development. PMID:25535249
Structural covariance networks in the mouse brain.
Pagani, Marco; Bifone, Angelo; Gozzi, Alessandro
2016-04-01
The presence of networks of correlation between regional gray matter volume as measured across subjects in a group of individuals has been consistently described in several human studies, an approach termed structural covariance MRI (scMRI). Complementary to prevalent brain mapping modalities like functional and diffusion-weighted imaging, the approach can provide precious insights into the mutual influence of trophic and plastic processes in health and pathological states. To investigate whether analogous scMRI networks are present in lower mammal species amenable to genetic and experimental manipulation such as the laboratory mouse, we employed high resolution morphoanatomical MRI in a large cohort of genetically-homogeneous wild-type mice (C57Bl6/J) and mapped scMRI networks using a seed-based approach. We show that the mouse brain exhibits robust homotopic scMRI networks in both primary and associative cortices, a finding corroborated by independent component analyses of cortical volumes. Subcortical structures also showed highly symmetric inter-hemispheric correlations, with evidence of distributed antero-posterior networks in diencephalic regions of the thalamus and hypothalamus. Hierarchical cluster analysis revealed six identifiable clusters of cortical and sub-cortical regions corresponding to previously described neuroanatomical systems. Our work documents the presence of homotopic cortical and subcortical scMRI networks in the mouse brain, thus supporting the use of this species to investigate the elusive biological and neuroanatomical underpinnings of scMRI network development and its derangement in neuropathological states. The identification of scMRI networks in genetically homogeneous inbred mice is consistent with the emerging view of a key role of environmental factors in shaping these correlational networks. PMID:26802512
Phase-covariant quantum benchmarks
Calsamiglia, J.; Aspachs, M.; Munoz-Tapia, R.; Bagan, E.
2009-05-15
We give a quantum benchmark for teleportation and quantum storage experiments suited for pure and mixed test states. The benchmark is based on the average fidelity over a family of phase-covariant states and certifies that an experiment cannot be emulated by a classical setup, i.e., by a measure-and-prepare scheme. We give an analytical solution for qubits, which shows important differences with standard state estimation approach, and compute the value of the benchmark for coherent and squeezed states, both pure and mixed.
Evaluation of Tungsten Nuclear Reaction Data with Covariances
Trkov, A. Capote, R.; Kodeli, I.; Leal, L.
2008-12-15
As a follow-up of the work presented at the ND-2007 conference in Nice, additional fast reactor benchmarks were analyzed. Adjustment to the cross sections in the keV region was necessary. Evaluated neutron cross section data files for {sup 180,182,183,184,186}W isotopes were produced. Covariances were generated for all isotopes except {sup 180}W. In the resonance range the retro-active method was used. Above the resolved resonance range the covariance prior was generated by the Monte Carlo technique from nuclear model calculations with the Empire-II code. Experimental data were taken into account through the GANDR system using the generalized least-squares technique. Introducing experimental data results in relatively small changes in the cross sections, but greatly constrains the uncertainties. The covariance files are currently undergoing testing.
Evaluation of Tungsten Nuclear Reaction Data with Covariances
Trkov, A.; Capote, R.; Kodeli, I.; Leal, Luiz C.
2008-12-01
As a follow-up of the work presented at the ND-2007 conference in Nice, additional fast reactor benchmarks were analyzed. Adjustment to the cross sections in the keV region was necessary. Evaluated neutron cross section data files for 180,182,183,184,186W isotopes were produced. Covariances were generated for all isotopes except 180W. In the resonance range the retro-active method was used. Above the resolved resonance range the covariance prior was generated by the Monte Carlo technique from nuclear model calculations with the Empire-II code. Experimental data were taken into account through the GANDR system using the generalized least-squares technique. Introducing experimental data results in relatively small changes in the cross sections, but greatly constrains the uncertainties. The covariance files are currently undergoing testing.
Neutron Cross Section Covariances for Structural Materials and Fission Products
NASA Astrophysics Data System (ADS)
Hoblit, S.; Cho, Y.-S.; Herman, M.; Mattoon, C. M.; Mughabghab, S. F.; Obložinský, P.; Pigni, M. T.; Sonzogni, A. A.
2011-12-01
We describe neutron cross section covariances for 78 structural materials and fission products produced for the new US evaluated nuclear reaction library ENDF/B-VII.1. Neutron incident energies cover full range from 10 eV to 20 MeV and covariances are primarily provided for capture, elastic and inelastic scattering as well as (n,2n). The list of materials follows priorities defined by the Advanced Fuel Cycle Initiative, the major application being data adjustment for advanced fast reactor systems. Thus, in addition to 28 structural materials and 49 fission products, the list includes also 23Na which is important fast reactor coolant. Due to extensive amount of materials, we adopted a variety of methodologies depending on the priority of a specific material. In the resolved resonance region we primarily used resonance parameter uncertainties given in Atlas of Neutron Resonances and either applied the kernel approximation to propagate these uncertainties into cross section uncertainties or resorted to simplified estimates based on integral quantities. For several priority materials we adopted MF32 covariances produced by SAMMY at ORNL, modified by us by adding MF33 covariances to account for systematic uncertainties. In the fast neutron region we resorted to three methods. The most sophisticated was EMPIRE-KALMAN method which combines experimental data from EXFOR library with nuclear reaction modeling and least-squares fitting. The two other methods used simplified estimates, either based on the propagation of nuclear reaction model parameter uncertainties or on a dispersion analysis of central cross section values in recent evaluated data files. All covariances were subject to quality assurance procedures adopted recently by CSEWG. In addition, tools were developed to allow inspection of processed covariances and computed integral quantities, and for comparing these values to data from the Atlas and the astrophysics database KADoNiS.
Neutron Cross Section Covariances for Structural Materials and Fission Products
Hoblit, S.; Hoblit,S.; Cho,Y.-S.; Herman,M.; Mattoon,C.M.; Mughabghab,S.F.; Oblozinsky,P.; Pigni,M.T.; Sonzogni,A.A.
2011-12-01
We describe neutron cross section covariances for 78 structural materials and fission products produced for the new US evaluated nuclear reaction library ENDF/B-VII.1. Neutron incident energies cover full range from 10{sup -5} eV to 20 MeV and covariances are primarily provided for capture, elastic and inelastic scattering as well as (n,2n). The list of materials follows priorities defined by the Advanced Fuel Cycle Initiative, the major application being data adjustment for advanced fast reactor systems. Thus, in addition to 28 structural materials and 49 fission products, the list includes also {sup 23}Na which is important fast reactor coolant. Due to extensive amount of materials, we adopted a variety of methodologies depending on the priority of a specific material. In the resolved resonance region we primarily used resonance parameter uncertainties given in Atlas of Neutron Resonances and either applied the kernel approximation to propagate these uncertainties into cross section uncertainties or resorted to simplified estimates based on integral quantities. For several priority materials we adopted MF32 covariances produced by SAMMY at ORNL, modified by us by adding MF33 covariances to account for systematic uncertainties. In the fast neutron region we resorted to three methods. The most sophisticated was EMPIRE-KALMAN method which combines experimental data from EXFOR library with nuclear reaction modeling and least-squares fitting. The two other methods used simplified estimates, either based on the propagation of nuclear reaction model parameter uncertainties or on a dispersion analysis of central cross section values in recent evaluated data files. All covariances were subject to quality assurance procedures adopted recently by CSEWG. In addition, tools were developed to allow inspection of processed covariances and computed integral quantities, and for comparing these values to data from the Atlas and the astrophysics database KADoNiS.
Yiannakouris, Nikos; Katsoulis, Michail; Trichopoulou, Antonia; Ordovas, Jose M; Trichopoulos, Dimitrios
2014-01-01
Objectives An additive genetic risk score (GRS) for coronary heart disease (CHD) has previously been associated with incident CHD in the population-based Greek European Prospective Investigation into Cancer and nutrition (EPIC) cohort. In this study, we explore GRS-‘environment’ joint actions on CHD for several conventional cardiovascular risk factors (ConvRFs), including smoking, hypertension, type-2 diabetes mellitus (T2DM), body mass index (BMI), physical activity and adherence to the Mediterranean diet. Design A case–control study. Setting The general Greek population of the EPIC study. Participants and outcome measures 477 patients with medically confirmed incident CHD and 1271 controls participated in this study. We estimated the ORs for CHD by dividing participants at higher or lower GRS and, alternatively, at higher or lower ConvRF, and calculated the relative excess risk due to interaction (RERI) as a measure of deviation from additivity. Results The joint presence of higher GRS and higher risk ConvRF was in all instances associated with an increased risk of CHD, compared with the joint presence of lower GRS and lower risk ConvRF. The OR (95% CI) was 1.7 (1.2 to 2.4) for smoking, 2.7 (1.9 to 3.8) for hypertension, 4.1 (2.8 to 6.1) for T2DM, 1.9 (1.4 to 2.5) for lower physical activity, 2.0 (1.3 to 3.2) for high BMI and 1.5 (1.1 to 2.1) for poor adherence to the Mediterranean diet. In all instances, RERI values were fairly small and not statistically significant, suggesting that the GRS and the ConvRFs do not have effects beyond additivity. Conclusions Genetic predisposition to CHD, operationalised through a multilocus GRS, and ConvRFs have essentially additive effects on CHD risk. PMID:24500614
Gao, H; Zhang, T; Wu, Y; Wu, Y; Jiang, L; Zhan, J; Li, J; Yang, R
2014-01-01
Given the drawbacks of implementing multivariate analysis for mapping multiple traits in genome-wide association study (GWAS), principal component analysis (PCA) has been widely used to generate independent ‘super traits' from the original multivariate phenotypic traits for the univariate analysis. However, parameter estimates in this framework may not be the same as those from the joint analysis of all traits, leading to spurious linkage results. In this paper, we propose to perform the PCA for residual covariance matrix instead of the phenotypical covariance matrix, based on which multiple traits are transformed to a group of pseudo principal components. The PCA for residual covariance matrix allows analyzing each pseudo principal component separately. In addition, all parameter estimates are equivalent to those obtained from the joint multivariate analysis under a linear transformation. However, a fast least absolute shrinkage and selection operator (LASSO) for estimating the sparse oversaturated genetic model greatly reduces the computational costs of this procedure. Extensive simulations show statistical and computational efficiencies of the proposed method. We illustrate this method in a GWAS for 20 slaughtering traits and meat quality traits in beef cattle. PMID:24984606
Singh, Sudhanshu; Mackill, David J; Ismail, Abdelbagi M
2014-01-01
1 lines. This suggests the possibility of further improvements in submergence tolerance by incorporating additional traits present in FR13A or other similar landraces. PMID:25281725
Singh, Sudhanshu; Mackill, David J.; Ismail, Abdelbagi M.
2014-01-01
1 lines. This suggests the possibility of further improvements in submergence tolerance by incorporating additional traits present in FR13A or other similar landraces. PMID:25281725
Parameter inference with estimated covariance matrices
NASA Astrophysics Data System (ADS)
Sellentin, Elena; Heavens, Alan F.
2016-02-01
When inferring parameters from a Gaussian-distributed data set by computing a likelihood, a covariance matrix is needed that describes the data errors and their correlations. If the covariance matrix is not known a priori, it may be estimated and thereby becomes a random object with some intrinsic uncertainty itself. We show how to infer parameters in the presence of such an estimated covariance matrix, by marginalizing over the true covariance matrix, conditioned on its estimated value. This leads to a likelihood function that is no longer Gaussian, but rather an adapted version of a multivariate t-distribution, which has the same numerical complexity as the multivariate Gaussian. As expected, marginalization over the true covariance matrix improves inference when compared with Hartlap et al.'s method, which uses an unbiased estimate of the inverse covariance matrix but still assumes that the likelihood is Gaussian.
COVARIANCE ASSISTED SCREENING AND ESTIMATION
Ke, By Tracy; Jin, Jiashun; Fan, Jianqing
2014-01-01
Consider a linear model Y = X β + z, where X = Xn,p and z ~ N(0, In). The vector β is unknown and it is of interest to separate its nonzero coordinates from the zero ones (i.e., variable selection). Motivated by examples in long-memory time series (Fan and Yao, 2003) and the change-point problem (Bhattacharya, 1994), we are primarily interested in the case where the Gram matrix G = X′X is non-sparse but sparsifiable by a finite order linear filter. We focus on the regime where signals are both rare and weak so that successful variable selection is very challenging but is still possible. We approach this problem by a new procedure called the Covariance Assisted Screening and Estimation (CASE). CASE first uses a linear filtering to reduce the original setting to a new regression model where the corresponding Gram (covariance) matrix is sparse. The new covariance matrix induces a sparse graph, which guides us to conduct multivariate screening without visiting all the submodels. By interacting with the signal sparsity, the graph enables us to decompose the original problem into many separated small-size subproblems (if only we know where they are!). Linear filtering also induces a so-called problem of information leakage, which can be overcome by the newly introduced patching technique. Together, these give rise to CASE, which is a two-stage Screen and Clean (Fan and Song, 2010; Wasserman and Roeder, 2009) procedure, where we first identify candidates of these submodels by patching and screening, and then re-examine each candidate to remove false positives. For any procedure β̂ for variable selection, we measure the performance by the minimax Hamming distance between the sign vectors of β̂ and β. We show that in a broad class of situations where the Gram matrix is non-sparse but sparsifiable, CASE achieves the optimal rate of convergence. The results are successfully applied to long-memory time series and the change-point model. PMID:25541567
Covariation and repeatability of male mating effort and mating preferences in a promiscuous fish
Godin, Jean-Guy J; Auld, Heather L
2013-01-01
Although mate choice by males does occur in nature, our understanding of its importance in driving evolutionary change remains limited compared with that for female mate choice. Recent theoretical models have shown that the evolution of male mate choice is more likely when individual variation in male mating effort and mating preferences exist and positively covary within populations. However, relatively little is known about the nature of such variation and its maintenance within natural populations. Here, using the Trinidadian guppy (Poecilia reticulata) as a model study system, we report that mating effort and mating preferences in males, based on female body length (a strong correlate of fecundity), positively covary and are significantly variable among subjects. Individual males are thus consistent, but not unanimous, in their mate choice. Both individual mating effort (including courtship effort) and mating preference were significantly repeatable. These novel findings support the assumptions and predictions of recent evolutionary models of male mate choice, and are consistent with the presence of additive genetic variation for male mate choice based on female size in our study population and thus with the opportunity for selection and further evolution of large female body size through male mate choice. PMID:23919148
Epigenetic Contribution to Covariance Between Relatives
Tal, Omri; Kisdi, Eva; Jablonka, Eva
2010-01-01
Recent research has pointed to the ubiquity and abundance of between-generation epigenetic inheritance. This research has implications for assessing disease risk and the responses to ecological stresses and also for understanding evolutionary dynamics. An important step toward a general evaluation of these implications is the identification and estimation of the amount of heritable, epigenetic variation in populations. While methods for modeling the phenotypic heritable variance contributed by culture have already been developed, there are no comparable methods for nonbehavioral epigenetic inheritance systems. By introducing a model that takes epigenetic transmissibility (the probability of transmission of ancestral phenotypes) and environmental induction into account, we provide novel expressions for covariances between relatives. We have combined a classical quantitative genetics approach with information about the number of opportunities for epigenetic reset between generations and assumptions about environmental induction to estimate the heritable epigenetic variance and epigenetic transmissibility for both asexual and sexual populations. This assists us in the identification of phenotypes and populations in which epigenetic transmission occurs and enables a preliminary quantification of their transmissibility, which could then be followed by genomewide association and QTL studies. PMID:20100941
Linkage analysis of anorexia nervosa incorporating behavioral covariates.
Devlin, Bernie; Bacanu, Silviu-Alin; Klump, Kelly L; Bulik, Cynthia M; Fichter, Manfred M; Halmi, Katherine A; Kaplan, Allan S; Strober, Michael; Treasure, Janet; Woodside, D Blake; Berrettini, Wade H; Kaye, Walter H
2002-03-15
Eating disorders, such as anorexia nervosa (AN) and bulimia nervosa (BN), have genetic and environmental underpinnings. To explore genetic contributions to AN, we measured psychiatric, personality and temperament phenotypes of individuals diagnosed with eating disorders from 196 multiplex families, all accessed through an AN proband, as well as genotyping a battery of 387 short tandem repeat (STR) markers distributed across the genome. On these data we performed a multipoint affected sibling pair (ASP) linkage analysis using a novel method that incorporates covariates. By exploring seven attributes thought to typify individuals with eating disorders, we identified two variables, drive-for-thinness and obsessionality, which delimit populations among the ASPs. For both of these traits, or covariates, there were a cluster of ASPs who have high and concordant values for these traits, in keeping with our expectations for individuals with AN, and other clusters of ASPs who did not meet those expectations. When we incorporated these covariates into the ASP linkage analysis, both jointly and separately, we found several regions of suggestive linkage: one close to genome-wide significance on chromosome 1 (at 210 cM, D1S1660; LOD = 3.46, P = 0.00003), another on chromosome 2 (at 114 cM, D2S1790; LOD = 2.22, P = 0.00070) and a third region on chromosome 13 (at 26 cM, D13S894; LOD = 2.50, P = 0.00035). By comparing our results to those implemented using more standard linkage methods, we find the covariates convey substantial information for the linkage analysis. PMID:11912184
Informed conditioning on clinical covariates increases power in case-control association studies.
Zaitlen, Noah; Lindström, Sara; Pasaniuc, Bogdan; Cornelis, Marilyn; Genovese, Giulio; Pollack, Samuela; Barton, Anne; Bickeböller, Heike; Bowden, Donald W; Eyre, Steve; Freedman, Barry I; Friedman, David J; Field, John K; Groop, Leif; Haugen, Aage; Heinrich, Joachim; Henderson, Brian E; Hicks, Pamela J; Hocking, Lynne J; Kolonel, Laurence N; Landi, Maria Teresa; Langefeld, Carl D; Le Marchand, Loic; Meister, Michael; Morgan, Ann W; Raji, Olaide Y; Risch, Angela; Rosenberger, Albert; Scherf, David; Steer, Sophia; Walshaw, Martin; Waters, Kevin M; Wilson, Anthony G; Wordsworth, Paul; Zienolddiny, Shanbeh; Tchetgen, Eric Tchetgen; Haiman, Christopher; Hunter, David J; Plenge, Robert M; Worthington, Jane; Christiani, David C; Schaumberg, Debra A; Chasman, Daniel I; Altshuler, David; Voight, Benjamin; Kraft, Peter; Patterson, Nick; Price, Alkes L
2012-01-01
Genetic case-control association studies often include data on clinical covariates, such as body mass index (BMI), smoking status, or age, that may modify the underlying genetic risk of case or control samples. For example, in type 2 diabetes, odds ratios for established variants estimated from low-BMI cases are larger than those estimated from high-BMI cases. An unanswered question is how to use this information to maximize statistical power in case-control studies that ascertain individuals on the basis of phenotype (case-control ascertainment) or phenotype and clinical covariates (case-control-covariate ascertainment). While current approaches improve power in studies with random ascertainment, they often lose power under case-control ascertainment and fail to capture available power increases under case-control-covariate ascertainment. We show that an informed conditioning approach, based on the liability threshold model with parameters informed by external epidemiological information, fully accounts for disease prevalence and non-random ascertainment of phenotype as well as covariates and provides a substantial increase in power while maintaining a properly controlled false-positive rate. Our method outperforms standard case-control association tests with or without covariates, tests of gene x covariate interaction, and previously proposed tests for dealing with covariates in ascertained data, with especially large improvements in the case of case-control-covariate ascertainment. We investigate empirical case-control studies of type 2 diabetes, prostate cancer, lung cancer, breast cancer, rheumatoid arthritis, age-related macular degeneration, and end-stage kidney disease over a total of 89,726 samples. In these datasets, informed conditioning outperforms logistic regression for 115 of the 157 known associated variants investigated (P-value = 1 × 10(-9)). The improvement varied across diseases with a 16% median increase in χ(2) test statistics and a
Rasul, Golam; Glover, Karl D; Krishnan, Padmanaban G; Wu, Jixiang; Berzonsky, William A; Ibrahim, Amir M H
2015-12-01
Elevated level of late maturity α-amylase activity (LMAA) can result in low falling number scores, reduced grain quality, and downgrade of wheat (Triticum aestivum L.) class. A mating population was developed by crossing parents with different levels of LMAA. The F2 and F3 hybrids and their parents were evaluated for LMAA, and data were analyzed using the R software package 'qgtools' integrated with an additive-dominance genetic model and a mixed linear model approach. Simulated results showed high testing powers for additive and additive × environment variances, and comparatively low powers for dominance and dominance × environment variances. All variance components and their proportions to the phenotypic variance for the parents and hybrids were significant except for the dominance × environment variance. The estimated narrow-sense heritability and broad-sense heritability for LMAA were 14 and 54%, respectively. High significant negative additive effects for parents suggest that spring wheat cultivars 'Lancer' and 'Chester' can serve as good general combiners, and that 'Kinsman' and 'Seri-82' had negative specific combining ability in some hybrids despite of their own significant positive additive effects, suggesting they can be used as parents to reduce LMAA levels. Seri-82 showed very good general combining ability effect when used as a male parent, indicating the importance of reciprocal effects. High significant negative dominance effects and high-parent heterosis for hybrids demonstrated that the specific hybrid combinations; Chester × Kinsman, 'Lerma52' × Lancer, Lerma52 × 'LoSprout' and 'Janz' × Seri-82 could be generated to produce cultivars with significantly reduced LMAA level. PMID:26403988
Particle emission from covariant phase space
Bambah, B.A. )
1992-12-01
Using Lorentz-covariant sources, we calculate the multiplicity distribution of {ital n} pair correlated particles emerging from a Lorentz-covariant phase-space volume. We use the Kim-Wigner formalism and identify these sources as the squeezed states of a relativistic harmonic oscillator. The applications of this to multiplicity distributions in particle physics is discussed.
Group Theory of Covariant Harmonic Oscillators
ERIC Educational Resources Information Center
Kim, Y. S.; Noz, Marilyn E.
1978-01-01
A simple and concrete example for illustrating the properties of noncompact groups is presented. The example is based on the covariant harmonic-oscillator formalism in which the relativistic wave functions carry a covariant-probability interpretation. This can be used in a group theory course for graduate students who have some background in…
Quality Quantification of Evaluated Cross Section Covariances
Varet, S.; Dossantos-Uzarralde, P.
2015-01-15
Presently, several methods are used to estimate the covariance matrix of evaluated nuclear cross sections. Because the resulting covariance matrices can be different according to the method used and according to the assumptions of the method, we propose a general and objective approach to quantify the quality of the covariance estimation for evaluated cross sections. The first step consists in defining an objective criterion. The second step is computation of the criterion. In this paper the Kullback-Leibler distance is proposed for the quality quantification of a covariance matrix estimation and its inverse. It is based on the distance to the true covariance matrix. A method based on the bootstrap is presented for the estimation of this criterion, which can be applied with most methods for covariance matrix estimation and without the knowledge of the true covariance matrix. The full approach is illustrated on the {sup 85}Rb nucleus evaluations and the results are then used for a discussion on scoring and Monte Carlo approaches for covariance matrix estimation of the cross section evaluations.
REGRESSION METHODS FOR DATA WITH INCOMPLETE COVARIATES
Modern statistical methods in chronic disease epidemiology allow simultaneous regression of disease status on several covariates. hese methods permit examination of the effects of one covariate while controlling for those of others that may be causally related to the disease. owe...
Ensemble Kalman filter implementations based on shrinkage covariance matrix estimation
NASA Astrophysics Data System (ADS)
Nino-Ruiz, Elias D.; Sandu, Adrian
2015-11-01
This paper develops efficient ensemble Kalman filter (EnKF) implementations based on shrinkage covariance estimation. The forecast ensemble members at each step are used to estimate the background error covariance matrix via the Rao-Blackwell Ledoit and Wolf estimator, which has been specifically developed to approximate high-dimensional covariance matrices using a small number of samples. Two implementations are considered: in the EnKF full-space (EnKF-FS) approach, the assimilation process is performed in the model space, while the EnKF reduce-space (EnKF-RS) formulation performs the analysis in the subspace spanned by the ensemble members. In the context of EnKF-RS, additional samples are taken from the normal distribution described by the background ensemble mean and the estimated background covariance matrix, in order to increase the size of the ensemble and reduce the sampling error of the filter. This increase in the size of the ensemble is obtained without running the forward model. After the assimilation step, the additional samples are discarded and only the model-based ensemble members are propagated further. Methodologies to reduce the impact of spurious correlations and under-estimation of sample variances in the context of the EnKF-FS and EnKF-RS implementations are discussed. An adjoint-free four-dimensional extension of EnKF-RS is also discussed. Numerical experiments carried out with the Lorenz-96 model and a quasi-geostrophic model show that the use of shrinkage covariance matrix estimation can mitigate the impact of spurious correlations during the assimilation process.
Effect modification by time-varying covariates.
Robins, James M; Hernán, Miguel A; Rotnitzky, Andrea
2007-11-01
Marginal structural models (MSMs) allow estimation of effect modification by baseline covariates, but they are less useful for estimating effect modification by evolving time-varying covariates. Rather, structural nested models (SNMs) were specifically designed to estimate effect modification by time-varying covariates. In their paper, Petersen et al. (Am J Epidemiol 2007;166:985-993) describe history-adjusted MSMs as a generalized form of MSM and argue that history-adjusted MSMs allow a researcher to easily estimate effect modification by time-varying covariates. However, history-adjusted MSMs can result in logically incompatible parameter estimates and hence in contradictory substantive conclusions. Here the authors propose a more restrictive definition of history-adjusted MSMs than the one provided by Petersen et al. and compare the advantages and disadvantages of using history-adjusted MSMs, as opposed to SNMs, to examine effect modification by time-dependent covariates. PMID:17875581
Adjoints and Low-rank Covariance Representation
NASA Technical Reports Server (NTRS)
Tippett, Michael K.; Cohn, Stephen E.
2000-01-01
Quantitative measures of the uncertainty of Earth System estimates can be as important as the estimates themselves. Second moments of estimation errors are described by the covariance matrix, whose direct calculation is impractical when the number of degrees of freedom of the system state is large. Ensemble and reduced-state approaches to prediction and data assimilation replace full estimation error covariance matrices by low-rank approximations. The appropriateness of such approximations depends on the spectrum of the full error covariance matrix, whose calculation is also often impractical. Here we examine the situation where the error covariance is a linear transformation of a forcing error covariance. We use operator norms and adjoints to relate the appropriateness of low-rank representations to the conditioning of this transformation. The analysis is used to investigate low-rank representations of the steady-state response to random forcing of an idealized discrete-time dynamical system.
Treatment decisions based on scalar and functional baseline covariates.
Ciarleglio, Adam; Petkova, Eva; Ogden, R Todd; Tarpey, Thaddeus
2015-12-01
The amount and complexity of patient-level data being collected in randomized-controlled trials offer both opportunities and challenges for developing personalized rules for assigning treatment for a given disease or ailment. For example, trials examining treatments for major depressive disorder are not only collecting typical baseline data such as age, gender, or scores on various tests, but also data that measure the structure and function of the brain such as images from magnetic resonance imaging (MRI), functional MRI (fMRI), or electroencephalography (EEG). These latter types of data have an inherent structure and may be considered as functional data. We propose an approach that uses baseline covariates, both scalars and functions, to aid in the selection of an optimal treatment. In addition to providing information on which treatment should be selected for a new patient, the estimated regime has the potential to provide insight into the relationship between treatment response and the set of baseline covariates. Our approach can be viewed as an extension of "advantage learning" to include both scalar and functional covariates. We describe our method and how to implement it using existing software. Empirical performance of our method is evaluated with simulated data in a variety of settings and also applied to data arising from a study of patients with major depressive disorder from whom baseline scalar covariates as well as functional data from EEG are available. PMID:26111145
Covariate-Adjusted Linear Mixed Effects Model with an Application to Longitudinal Data
Nguyen, Danh V.; Şentürk, Damla; Carroll, Raymond J.
2009-01-01
Linear mixed effects (LME) models are useful for longitudinal data/repeated measurements. We propose a new class of covariate-adjusted LME models for longitudinal data that nonparametrically adjusts for a normalizing covariate. The proposed approach involves fitting a parametric LME model to the data after adjusting for the nonparametric effects of a baseline confounding covariate. In particular, the effect of the observable covariate on the response and predictors of the LME model is modeled nonparametrically via smooth unknown functions. In addition to covariate-adjusted estimation of fixed/population parameters and random effects, an estimation procedure for the variance components is also developed. Numerical properties of the proposed estimators are investigated with simulation studies. The consistency and convergence rates of the proposed estimators are also established. An application to a longitudinal data set on calcium absorption, accounting for baseline distortion from body mass index, illustrates the proposed methodology. PMID:19266053
Exploring Eddy-Covariance Measurements Using a Spatial Approach: The Eddy Matrix
NASA Astrophysics Data System (ADS)
Engelmann, Christian; Bernhofer, Christian
2016-04-01
Taylor's frozen turbulence hypothesis states that "standard" eddy-covariance measurements of fluxes at a fixed location can replace a spatial ensemble of instantaneous values at multiple locations. For testing this hypothesis, a unique turbulence measurement set-up was used for two measurement campaigns over desert (Namibia) and grassland (Germany) in 2012. This "Eddy Matrix" combined nine ultrasonic anemometer-thermometers and 17 thermocouples in a 10 m × 10 m regular grid with 2.5-m grid distance. The instantaneous buoyancy flux derived from the spatial eddy covariance of the Eddy Matrix was highly variable in time (from -0.3 to 1 m K s^{-1} ). However, the 10-min average reflected 83 % of the reference eddy-covariance flux with a good correlation. By introducing a combined eddy-covariance method (the spatial eddy covariance plus the additional flux of the temporal eddy covariance of the spatial mean values), the mean flux increases by 9 % relative to the eddy-covariance reference. Considering the typical underestimation of fluxes by the standard eddy-covariance method, this is seen as an improvement. Within the limits of the Eddy Matrix, Taylor's hypothesis is supported by the results.
Lagishetty, Chakradhar V; Duffull, Stephen B
2015-11-01
Clinical studies include occurrences of rare variables, like genotypes, which due to their frequency and strength render their effects difficult to estimate from a dataset. Variables that influence the estimated value of a model-based parameter are termed covariates. It is often difficult to determine if such an effect is significant, since type I error can be inflated when the covariate is rare. Their presence may have either an insubstantial effect on the parameters of interest, hence are ignorable, or conversely they may be influential and therefore non-ignorable. In the case that these covariate effects cannot be estimated due to power and are non-ignorable, then these are considered nuisance, in that they have to be considered but due to type 1 error are of limited interest. This study assesses methods of handling nuisance covariate effects. The specific objectives include (1) calibrating the frequency of a covariate that is associated with type 1 error inflation, (2) calibrating its strength that renders it non-ignorable and (3) evaluating methods for handling these non-ignorable covariates in a nonlinear mixed effects model setting. Type 1 error was determined for the Wald test. Methods considered for handling the nuisance covariate effects were case deletion, Box-Cox transformation and inclusion of a specific fixed effects parameter. Non-ignorable nuisance covariates were found to be effectively handled through addition of a fixed effect parameter. PMID:26112250
The covariate-adjusted frequency plot.
Holling, Heinz; Böhning, Walailuck; Böhning, Dankmar; Formann, Anton K
2016-04-01
Count data arise in numerous fields of interest. Analysis of these data frequently require distributional assumptions. Although the graphical display of a fitted model is straightforward in the univariate scenario, this becomes more complex if covariate information needs to be included into the model. Stratification is one way to proceed, but has its limitations if the covariate has many levels or the number of covariates is large. The article suggests a marginal method which works even in the case that all possible covariate combinations are different (i.e. no covariate combination occurs more than once). For each covariate combination the fitted model value is computed and then summed over the entire data set. The technique is quite general and works with all count distributional models as well as with all forms of covariate modelling. The article provides illustrations of the method for various situations and also shows that the proposed estimator as well as the empirical count frequency are consistent with respect to the same parameter. PMID:23376964
Relativistically Covariant Many-Body Perturbation Procedure
NASA Astrophysics Data System (ADS)
Lindgren, Ingvar; Salomonson, Sten; Hedendahl, Daniel
A covariant evolution operator (CEO) can be constructed, representing the time evolution of the relativistic wave unction or state vector. Like the nonrelativistic version, it contains (quasi-)singularities. The regular part is referred to as the Green’s operator (GO), which is the operator analogue of the Green’s function (GF). This operator, which is a field-theoretical concept, is closely related to the many-body wave operator and effective Hamiltonian, and it is the basic tool for our unified theory. The GO leads, when the perturbation is carried to all orders, to the Bethe-Salpeter equation (BSE) in the equal-time or effective-potential approximation. When relaxing the equal-time restriction, the procedure is fully compatible with the exact BSE. The calculations are performed in the photonic Fock space, where the number of photons is no longer constant. The procedure has been applied to helium-like ions, and the results agree well with S-matrix results in cases when comparison can be performed. In addition, evaluation of higher-order quantum-electrodynamical (QED) correlational effects has been performed, and the effects are found to be quite significant for light and medium-heavy ions.
Covariation bias in panic-prone individuals.
Pauli, P; Montoya, P; Martz, G E
1996-11-01
Covariation estimates between fear-relevant (FR; emergency situations) or fear-irrelevant (FI; mushrooms and nudes) stimuli and an aversive outcome (electrical shock) were examined in 10 high-fear (panic-prone) and 10 low-fear respondents. When the relation between slide category and outcome was random (illusory correlation), only high-fear participants markedly overestimated the contingency between FR slides and shocks. However, when there was a high contingency of shocks following FR stimuli (83%) and a low contingency of shocks following FI stimuli (17%), the group difference vanished. Reversal of contingencies back to random induced a covariation bias for FR slides in high- and low-fear respondents. Results indicate that panic-prone respondents show a covariation bias for FR stimuli and that the experience of a high contingency between FR slides and aversive outcomes may foster such a covariation bias even in low-fear respondents. PMID:8952200
Reconciling Covariances with Reliable Orbital Uncertainty
NASA Astrophysics Data System (ADS)
Folcik, Z.; Lue, A.; Vatsky, J.
2011-09-01
There is a common suspicion that formal covariances do not represent a realistic measure of orbital uncertainties. By devising metrics for measuring the representations of orbit error, we assess under what circumstances such lore is justified as well as the root cause of the discrepancy between the mathematics of orbital uncertainty and its practical implementation. We offer a scheme by which formal covariances may be adapted to be an accurate measure of orbital uncertainties and show how that adaptation performs against both simulated and real space-object data. We also apply these covariance adaptation methods to the process of observation association using many simulated and real data test cases. We demonstrate that covariance-informed observation association can be reliable, even in the case when only two tracks are available. Satellite breakup and collision event catalog maintenance could benefit from the automation made possible with these association methods.
Noncommutative Gauge Theory with Covariant Star Product
Zet, G.
2010-08-04
We present a noncommutative gauge theory with covariant star product on a space-time with torsion. In order to obtain the covariant star product one imposes some restrictions on the connection of the space-time. Then, a noncommutative gauge theory is developed applying this product to the case of differential forms. Some comments on the advantages of using a space-time with torsion to describe the gravitational field are also given.
Covariant action for type IIB supergravity
NASA Astrophysics Data System (ADS)
Sen, Ashoke
2016-07-01
Taking clues from the recent construction of the covariant action for type II and heterotic string field theories, we construct a manifestly Lorentz covariant action for type IIB supergravity, and discuss its gauge fixing maintaining manifest Lorentz invariance. The action contains a (non-gravitating) free 4-form field besides the usual fields of type IIB supergravity. This free field, being completely decoupled from the interacting sector, has no physical consequence.
Phase-covariant quantum cloning of qudits
Fan Heng; Imai, Hiroshi; Matsumoto, Keiji; Wang, Xiang-Bin
2003-02-01
We study the phase-covariant quantum cloning machine for qudits, i.e., the input states in a d-level quantum system have complex coefficients with arbitrary phase but constant module. A cloning unitary transformation is proposed. After optimizing the fidelity between input state and single qudit reduced density operator of output state, we obtain the optimal fidelity for 1 to 2 phase-covariant quantum cloning of qudits and the corresponding cloning transformation.
Low-dimensional Representation of Error Covariance
NASA Technical Reports Server (NTRS)
Tippett, Michael K.; Cohn, Stephen E.; Todling, Ricardo; Marchesin, Dan
2000-01-01
Ensemble and reduced-rank approaches to prediction and assimilation rely on low-dimensional approximations of the estimation error covariances. Here stability properties of the forecast/analysis cycle for linear, time-independent systems are used to identify factors that cause the steady-state analysis error covariance to admit a low-dimensional representation. A useful measure of forecast/analysis cycle stability is the bound matrix, a function of the dynamics, observation operator and assimilation method. Upper and lower estimates for the steady-state analysis error covariance matrix eigenvalues are derived from the bound matrix. The estimates generalize to time-dependent systems. If much of the steady-state analysis error variance is due to a few dominant modes, the leading eigenvectors of the bound matrix approximate those of the steady-state analysis error covariance matrix. The analytical results are illustrated in two numerical examples where the Kalman filter is carried to steady state. The first example uses the dynamics of a generalized advection equation exhibiting nonmodal transient growth. Failure to observe growing modes leads to increased steady-state analysis error variances. Leading eigenvectors of the steady-state analysis error covariance matrix are well approximated by leading eigenvectors of the bound matrix. The second example uses the dynamics of a damped baroclinic wave model. The leading eigenvectors of a lowest-order approximation of the bound matrix are shown to approximate well the leading eigenvectors of the steady-state analysis error covariance matrix.
Adjusting for matching and covariates in linear discriminant analysis
Asafu-Adjei, Josephine K.; Sampson, Allan R.; Sweet, Robert A.; Lewis, David A.
2013-01-01
In studies that compare several diagnostic or treatment groups, subjects may not only be measured on a certain set of feature variables, but also be matched on a number of demographic characteristics and measured on additional covariates. Linear discriminant analysis (LDA) is sometimes used to identify which feature variables best discriminate among groups, while accounting for the dependencies among the feature variables. We present a new approach to LDA for multivariate normal data that accounts for the subject matching used in a particular study design, as well as covariates not used in the matching. Applications are given for post-mortem tissue data with the aim of comparing neurobiological characteristics of subjects with schizophrenia with those of normal controls, and for a post-mortem tissue primate study comparing brain biomarker measurements across three treatment groups. We also investigate the performance of our approach using a simulation study. PMID:23640791
Covariant Tarpeian Method for Bloat Control in Genetic Programming
NASA Astrophysics Data System (ADS)
Poli, Riccardo
In this paper a simple modification of the Tarpeian bloat-control method is presented which allows one to dynamically set the parameters of the method in such a way to guarantee that the mean program size will either keep a particular value (e.g., its initial value) or will follow a schedule chosen by the user. The mathematical derivation of the technique as well as its numerical and empirical corroboration are presented.
Genome-Wide Networks of Amino Acid Covariances Are Common among Viruses
Donlin, Maureen J.; Szeto, Brandon; Gohara, David W.; Aurora, Rajeev
2012-01-01
Coordinated variation among positions in amino acid sequence alignments can reveal genetic dependencies at noncontiguous positions, but methods to assess these interactions are incompletely developed. Previously, we found genome-wide networks of covarying residue positions in the hepatitis C virus genome (R. Aurora, M. J. Donlin, N. A. Cannon, and J. E. Tavis, J. Clin. Invest. 119:225–236, 2009). Here, we asked whether such networks are present in a diverse set of viruses and, if so, what they may imply about viral biology. Viral sequences were obtained for 16 viruses in 13 species from 9 families. The entire viral coding potential for each virus was aligned, all possible amino acid covariances were identified using the observed-minus-expected-squared algorithm at a false-discovery rate of ≤1%, and networks of covariances were assessed using standard methods. Covariances that spanned the viral coding potential were common in all viruses. In all cases, the covariances formed a single network that contained essentially all of the covariances. The hepatitis C virus networks had hub-and-spoke topologies, but all other networks had random topologies with an unusually large number of highly connected nodes. These results indicate that genome-wide networks of genetic associations and the coordinated evolution they imply are very common in viral genomes, that the networks rarely have the hub-and-spoke topology that dominates other biological networks, and that network topologies can vary substantially even within a given viral group. Five examples with hepatitis B virus and poliovirus are presented to illustrate how covariance network analysis can lead to inferences about viral biology. PMID:22238298
Few, Lauren R.; Grant, Julia D; Trull, Timothy J.; Statham, Dixie J.; Martin, Nicholas G.; Lynskey, Michael T.; Agrawal, Arpana
2014-01-01
Aims To examine the genetic overlap between borderline personality features (BPF) and substance use disorders (SUDs) and the extent to which variation in personality traits contributes to this covariance. Design Genetic structural equation modelling was used to partition the variance in and covariance between personality traits, BPF, and SUDs into additive genetic, shared, and individual-specific environmental factors. Setting All participants were registered with the Australian Twin Registry. Participants A total of 3,127 Australian adult twins participated in the study. Measurements Diagnoses of DSM-IV alcohol and cannabis abuse/dependence (AAD; CAD), and nicotine dependence (ND) were derived via computer-assisted telephone interview. BPF and five-factor model personality traits were derived via self-report questionnaires. Findings Genetic factors were responsible for 49% (95%CI: 42%–55%) of the variance in BPF, 38–42% (95%CI range: 32%–49%) for personality traits and 47% (95%CI: 17%–77%), 54% (95%CI: 43%–64%), and 78% (67%–86%) for ND, AAD and CAD, respectively. Genetic and individual-specific environmental correlations between BPF and SUDs ranged from .33–.56 (95%CI range: .19–.74) and .19–.32 (95%CI range: .06–.43), respectively. Overall, there was substantial support for genetic influences that were specific to AAD, ND and CAD (31%–69%). Finally, genetic variation in personality traits was responsible for 11% (Extraversion for CAD) to 59% (Neuroticism for AAD) of the correlation between BPF and SUDs. Conclusions Both genetic and individual-specific environmental factors contribute to comorbidity between borderline personality features and substance use disorders. A substantial proportion of this comorbidity can be attributed to variation in normal personality traits, particularly Neuroticism. PMID:25041562
Schillebeeckx, P.; Becker, B.; Danon, Y.; Guber, K.; Harada, H.; Heyse, J.; Junghans, A.R.; Kopecky, S.; Massimi, C.; Moxon, M.C.; Otuka, N.; Sirakov, I.; Volev, K.
2012-12-15
Cross section data in the resolved and unresolved resonance region are represented by nuclear reaction formalisms using parameters which are determined by fitting them to experimental data. Therefore, the quality of evaluated cross sections in the resonance region strongly depends on the experimental data used in the adjustment process and an assessment of the experimental covariance data is of primary importance in determining the accuracy of evaluated cross section data. In this contribution, uncertainty components of experimental observables resulting from total and reaction cross section experiments are quantified by identifying the metrological parameters involved in the measurement, data reduction and analysis process. In addition, different methods that can be applied to propagate the covariance of the experimental observables (i.e. transmission and reaction yields) to the covariance of the resonance parameters are discussed and compared. The methods being discussed are: conventional uncertainty propagation, Monte Carlo sampling and marginalization. It is demonstrated that the final covariance matrix of the resonance parameters not only strongly depends on the type of experimental observables used in the adjustment process, the experimental conditions and the characteristics of the resonance structure, but also on the method that is used to propagate the covariances. Finally, a special data reduction concept and format is presented, which offers the possibility to store the full covariance information of experimental data in the EXFOR library and provides the information required to perform a full covariance evaluation.
Spacetime states and covariant quantum theory
NASA Astrophysics Data System (ADS)
Reisenberger, Michael; Rovelli, Carlo
2002-06-01
In its usual presentation, classical mechanics appears to give time a very special role. But it is well known that mechanics can be formulated so as to treat the time variable on the same footing as the other variables in the extended configuration space. Such covariant formulations are natural for relativistic gravitational systems, where general covariance conflicts with the notion of a preferred physical-time variable. The standard presentation of quantum mechanics, in turn, again gives time a very special role, raising well known difficulties for quantum gravity. Is there a covariant form of (canonical) quantum mechanics? We observe that the preferred role of time in quantum theory is the consequence of an idealization: that measurements are instantaneous. Canonical quantum theory can be given a covariant form by dropping this idealization. States prepared by noninstantaneous measurements are described by ``spacetime smeared states.'' The theory can be formulated in terms of these states, without making any reference to a special time variable. The quantum dynamics is expressed in terms of the propagator, an object covariantly defined on the extended configuration space.
Bilinear covariants and spinor fields duality in quantum Clifford algebras
Abłamowicz, Rafał; Gonçalves, Icaro; Rocha, Roldão da
2014-10-15
Classification of quantum spinor fields according to quantum bilinear covariants is introduced in a context of quantum Clifford algebras on Minkowski spacetime. Once the bilinear covariants are expressed in terms of algebraic spinor fields, the duality between spinor and quantum spinor fields can be discussed. Thus, by endowing the underlying spacetime with an arbitrary bilinear form with an antisymmetric part in addition to a symmetric spacetime metric, quantum algebraic spinor fields and deformed bilinear covariants can be constructed. They are thus compared to the classical (non quantum) ones. Classes of quantum spinor fields classes are introduced and compared with Lounesto's spinor field classification. A physical interpretation of the deformed parts and the underlying Z-grading is proposed. The existence of an arbitrary bilinear form endowing the spacetime already has been explored in the literature in the context of quantum gravity [S. W. Hawking, “The unpredictability of quantum gravity,” Commun. Math. Phys. 87, 395 (1982)]. Here, it is shown further to play a prominent role in the structure of Dirac, Weyl, and Majorana spinor fields, besides the most general flagpoles and flag-dipoles. We introduce a new duality between the standard and the quantum spinor fields, by showing that when Clifford algebras over vector spaces endowed with an arbitrary bilinear form are taken into account, a mixture among the classes does occur. Consequently, novel features regarding the spinor fields can be derived.
Defining habitat covariates in camera-trap based occupancy studies
Niedballa, Jürgen; Sollmann, Rahel; Mohamed, Azlan bin; Bender, Johannes; Wilting, Andreas
2015-01-01
In species-habitat association studies, both the type and spatial scale of habitat covariates need to match the ecology of the focal species. We assessed the potential of high-resolution satellite imagery for generating habitat covariates using camera-trapping data from Sabah, Malaysian Borneo, within an occupancy framework. We tested the predictive power of covariates generated from satellite imagery at different resolutions and extents (focal patch sizes, 10–500 m around sample points) on estimates of occupancy patterns of six small to medium sized mammal species/species groups. High-resolution land cover information had considerably more model support for small, patchily distributed habitat features, whereas it had no advantage for large, homogeneous habitat features. A comparison of different focal patch sizes including remote sensing data and an in-situ measure showed that patches with a 50-m radius had most support for the target species. Thus, high-resolution satellite imagery proved to be particularly useful in heterogeneous landscapes, and can be used as a surrogate for certain in-situ measures, reducing field effort in logistically challenging environments. Additionally, remote sensed data provide more flexibility in defining appropriate spatial scales, which we show to impact estimates of wildlife-habitat associations. PMID:26596779
Bilinear covariants and spinor fields duality in quantum Clifford algebras
NASA Astrophysics Data System (ADS)
Abłamowicz, Rafał; Gonçalves, Icaro; da Rocha, Roldão
2014-10-01
Classification of quantum spinor fields according to quantum bilinear covariants is introduced in a context of quantum Clifford algebras on Minkowski spacetime. Once the bilinear covariants are expressed in terms of algebraic spinor fields, the duality between spinor and quantum spinor fields can be discussed. Thus, by endowing the underlying spacetime with an arbitrary bilinear form with an antisymmetric part in addition to a symmetric spacetime metric, quantum algebraic spinor fields and deformed bilinear covariants can be constructed. They are thus compared to the classical (non quantum) ones. Classes of quantum spinor fields classes are introduced and compared with Lounesto's spinor field classification. A physical interpretation of the deformed parts and the underlying {Z}-grading is proposed. The existence of an arbitrary bilinear form endowing the spacetime already has been explored in the literature in the context of quantum gravity [S. W. Hawking, "The unpredictability of quantum gravity," Commun. Math. Phys. 87, 395 (1982)]. Here, it is shown further to play a prominent role in the structure of Dirac, Weyl, and Majorana spinor fields, besides the most general flagpoles and flag-dipoles. We introduce a new duality between the standard and the quantum spinor fields, by showing that when Clifford algebras over vector spaces endowed with an arbitrary bilinear form are taken into account, a mixture among the classes does occur. Consequently, novel features regarding the spinor fields can be derived.
GPU implementations for fast factorizations of STAP covariance matrices
NASA Astrophysics Data System (ADS)
Roeder, Michael; Davis, Nolan; Furtek, Jeremy; Braunreiter, Dennis; Healy, Dennis
2008-08-01
One of the main goals of the STAP-BOY program has been the implementation of a space-time adaptive processing (STAP) algorithm on graphics processing units (GPUs) with the goal of reducing the processing time. Within the context of GPU implementation, we have further developed algorithms that exploit data redundancy inherent in particular STAP applications. Integration of these algorithms with GPU architecture is of primary importance for fast algorithmic processing times. STAP algorithms involve solving a linear system in which the transformation matrix is a covariance matrix. A standard method involves estimating a covariance matrix from a data matrix, computing its Cholesky factors by one of several methods, and then solving the system by substitution. Some STAP applications have redundancy in successive data matrices from which the covariance matrices are formed. For STAP applications in which a data matrix is updated with the addition of a new data row at the bottom and the elimination of the oldest data in the top of the matrix, a sequence of data matrices have multiple rows in common. Two methods have been developed for exploiting this type of data redundancy when computing Cholesky factors. These two methods are referred to as 1) Fast QR factorizations of successive data matrices 2) Fast Cholesky factorizations of successive covariance matrices. We have developed GPU implementations of these two methods. We show that these two algorithms exhibit reduced computational complexity when compared to benchmark algorithms that do not exploit data redundancy. More importantly, we show that when these algorithmic improvements are optimized for the GPU architecture, the processing times of a GPU implementation of these matrix factorization algorithms may be greatly improved.
Influence of mom and dad: quantitative genetic models for maternal effects and genomic imprinting.
Santure, Anna W; Spencer, Hamish G
2006-08-01
The expression of an imprinted gene is dependent on the sex of the parent it was inherited from, and as a result reciprocal heterozygotes may display different phenotypes. In contrast, maternal genetic terms arise when the phenotype of an offspring is influenced by the phenotype of its mother beyond the direct inheritance of alleles. Both maternal effects and imprinting may contribute to resemblance between offspring of the same mother. We demonstrate that two standard quantitative genetic models for deriving breeding values, population variances and covariances between relatives, are not equivalent when maternal genetic effects and imprinting are acting. Maternal and imprinting effects introduce both sex-dependent and generation-dependent effects that result in differences in the way additive and dominance effects are defined for the two approaches. We use a simple example to demonstrate that both imprinting and maternal genetic effects add extra terms to covariances between relatives and that model misspecification may over- or underestimate true covariances or lead to extremely variable parameter estimation. Thus, an understanding of various forms of parental effects is essential in correctly estimating quantitative genetic variance components. PMID:16751674
FAST NEUTRON COVARIANCES FOR EVALUATED DATA FILES.
HERMAN, M.; OBLOZINSKY, P.; ROCHMAN, D.; KAWANO, T.; LEAL, L.
2006-06-05
We describe implementation of the KALMAN code in the EMPIRE system and present first covariance data generated for Gd and Ir isotopes. A complete set of covariances, in the full energy range, was produced for the chain of 8 Gadolinium isotopes for total, elastic, capture, total inelastic (MT=4), (n,2n), (n,p) and (n,alpha) reactions. Our correlation matrices, based on combination of model calculations and experimental data, are characterized by positive mid-range and negative long-range correlations. They differ from the model-generated covariances that tend to show strong positive long-range correlations and those determined solely from experimental data that result in nearly diagonal matrices. We have studied shapes of correlation matrices obtained in the calculations and interpreted them in terms of the underlying reaction models. An important result of this study is the prediction of narrow energy ranges with extremely small uncertainties for certain reactions (e.g., total and elastic).
Gram-Schmidt algorithms for covariance propagation
NASA Technical Reports Server (NTRS)
Thornton, C. L.; Bierman, G. J.
1977-01-01
This paper addresses the time propagation of triangular covariance factors. Attention is focused on the square-root free factorization, P = UD(transpose of U), where U is unit upper triangular and D is diagonal. An efficient and reliable algorithm for U-D propagation is derived which employs Gram-Schmidt orthogonalization. Partitioning the state vector to distinguish bias and coloured process noise parameters increase mapping efficiency. Cost comparisons of the U-D, Schmidt square-root covariance and conventional covariance propagation methods are made using weighted arithmetic operation counts. The U-D time update is shown to be less costly than the Schmidt method; and, except in unusual circumstances, it is within 20% of the cost of conventional propagation.
Gram-Schmidt algorithms for covariance propagation
NASA Technical Reports Server (NTRS)
Thornton, C. L.; Bierman, G. J.
1975-01-01
This paper addresses the time propagation of triangular covariance factors. Attention is focused on the square-root free factorization, P = UDU/T/, where U is unit upper triangular and D is diagonal. An efficient and reliable algorithm for U-D propagation is derived which employs Gram-Schmidt orthogonalization. Partitioning the state vector to distinguish bias and colored process noise parameters increases mapping efficiency. Cost comparisons of the U-D, Schmidt square-root covariance and conventional covariance propagation methods are made using weighted arithmetic operation counts. The U-D time update is shown to be less costly than the Schmidt method; and, except in unusual circumstances, it is within 20% of the cost of conventional propagation.
Parametric number covariance in quantum chaotic spectra
NASA Astrophysics Data System (ADS)
Vinayak, Kumar, Sandeep; Pandey, Akhilesh
2016-03-01
We study spectral parametric correlations in quantum chaotic systems and introduce the number covariance as a measure of such correlations. We derive analytic results for the classical random matrix ensembles using the binary correlation method and obtain compact expressions for the covariance. We illustrate the universality of this measure by presenting the spectral analysis of the quantum kicked rotors for the time-reversal invariant and time-reversal noninvariant cases. A local version of the parametric number variance introduced earlier is also investigated.
Covariant Spectator Theory and Hadron Structure
NASA Astrophysics Data System (ADS)
Peña, M. T.; Leitão, Sofia; Biernat, Elmar P.; Stadler, Alfred; Ribeiro, J. E.; Gross, Franz
2016-06-01
We present the first results of a study on meson spectroscopy using a covariant formalism based on the Covariant Spectator Theory. Our approach is derived directly in Minkowski space and it approximates the Bethe-Salpeter equation by taking effectively into account the contributions from both ladder and crossed ladder diagrams in the q{bar{q}} interaction kernel. A general Lorentz structure of the kernel is tested and chiral constraints on the kernel are discussed. Results for the pion form factor are also presented.
A violation of the covariant entropy bound?
NASA Astrophysics Data System (ADS)
Masoumi, Ali; Mathur, Samir D.
2015-04-01
Several arguments suggest that the entropy density at high energy density ρ should be given by the expression s =K √{ρ /G } , where K is a constant of order unity. On the other hand the covariant entropy bound requires that the entropy on a light sheet be bounded by A /4 G , where A is the area of the boundary of the sheet. We find that in a suitably chosen cosmological geometry, the above expression for s violates the covariant entropy bound. We consider different possible explanations for this fact, in particular, the possibility that entropy bounds should be defined in terms of volumes of regions rather than areas of surfaces.
Covariance Analysis of Gamma Ray Spectra
Trainham, R.; Tinsley, J.
2013-01-01
The covariance method exploits fluctuations in signals to recover information encoded in correlations which are usually lost when signal averaging occurs. In nuclear spectroscopy it can be regarded as a generalization of the coincidence technique. The method can be used to extract signal from uncorrelated noise, to separate overlapping spectral peaks, to identify escape peaks, to reconstruct spectra from Compton continua, and to generate secondary spectral fingerprints. We discuss a few statistical considerations of the covariance method and present experimental examples of its use in gamma spectroscopy.
Covariance analysis of gamma ray spectra
Trainham, R.; Tinsley, J.
2013-01-15
The covariance method exploits fluctuations in signals to recover information encoded in correlations which are usually lost when signal averaging occurs. In nuclear spectroscopy it can be regarded as a generalization of the coincidence technique. The method can be used to extract signal from uncorrelated noise, to separate overlapping spectral peaks, to identify escape peaks, to reconstruct spectra from Compton continua, and to generate secondary spectral fingerprints. We discuss a few statistical considerations of the covariance method and present experimental examples of its use in gamma spectroscopy.
Sparse Multivariate Regression With Covariance Estimation
Rothman, Adam J.; Levina, Elizaveta; Zhu, Ji
2014-01-01
We propose a procedure for constructing a sparse estimator of a multivariate regression coefficient matrix that accounts for correlation of the response variables. This method, which we call multivariate regression with covariance estimation (MRCE), involves penalized likelihood with simultaneous estimation of the regression coefficients and the covariance structure. An efficient optimization algorithm and a fast approximation are developed for computing MRCE. Using simulation studies, we show that the proposed method outperforms relevant competitors when the responses are highly correlated. We also apply the new method to a finance example on predicting asset returns. An R-package containing this dataset and code for computing MRCE and its approximation are available online. PMID:24963268
Parametric number covariance in quantum chaotic spectra.
Vinayak; Kumar, Sandeep; Pandey, Akhilesh
2016-03-01
We study spectral parametric correlations in quantum chaotic systems and introduce the number covariance as a measure of such correlations. We derive analytic results for the classical random matrix ensembles using the binary correlation method and obtain compact expressions for the covariance. We illustrate the universality of this measure by presenting the spectral analysis of the quantum kicked rotors for the time-reversal invariant and time-reversal noninvariant cases. A local version of the parametric number variance introduced earlier is also investigated. PMID:27078354
NASA Astrophysics Data System (ADS)
Roslund, Jonathan; Shir, Ofer M.; Bäck, Thomas; Rabitz, Herschel
2009-10-01
Optimization of quantum systems by closed-loop adaptive pulse shaping offers a rich domain for the development and application of specialized evolutionary algorithms. Derandomized evolution strategies (DESs) are presented here as a robust class of optimizers for experimental quantum control. The combination of stochastic and quasi-local search embodied by these algorithms is especially amenable to the inherent topology of quantum control landscapes. Implementation of DES in the laboratory results in efficiency gains of up to ˜9 times that of the standard genetic algorithm, and thus is a promising tool for optimization of unstable or fragile systems. The statistical learning upon which these algorithms are predicated also provide the means for obtaining a control problem’s Hessian matrix with no additional experimental overhead. The forced optimal covariance adaptive learning (FOCAL) method is introduced to enable retrieval of the Hessian matrix, which can reveal information about the landscape’s local structure and dynamic mechanism. Exploitation of such algorithms in quantum control experiments should enhance their efficiency and provide additional fundamental insights.
Roslund, Jonathan; Shir, Ofer M.; Rabitz, Herschel; Baeck, Thomas
2009-10-15
Optimization of quantum systems by closed-loop adaptive pulse shaping offers a rich domain for the development and application of specialized evolutionary algorithms. Derandomized evolution strategies (DESs) are presented here as a robust class of optimizers for experimental quantum control. The combination of stochastic and quasi-local search embodied by these algorithms is especially amenable to the inherent topology of quantum control landscapes. Implementation of DES in the laboratory results in efficiency gains of up to {approx}9 times that of the standard genetic algorithm, and thus is a promising tool for optimization of unstable or fragile systems. The statistical learning upon which these algorithms are predicated also provide the means for obtaining a control problem's Hessian matrix with no additional experimental overhead. The forced optimal covariance adaptive learning (FOCAL) method is introduced to enable retrieval of the Hessian matrix, which can reveal information about the landscape's local structure and dynamic mechanism. Exploitation of such algorithms in quantum control experiments should enhance their efficiency and provide additional fundamental insights.
Predicting Genetic Values: A Kernel-Based Best Linear Unbiased Prediction With Genomic Data
Ober, Ulrike; Erbe, Malena; Long, Nanye; Porcu, Emilio; Schlather, Martin; Simianer, Henner
2011-01-01
Genomic data provide a valuable source of information for modeling covariance structures, allowing a more accurate prediction of total genetic values (GVs). We apply the kriging concept, originally developed in the geostatistical context for predictions in the low-dimensional space, to the high-dimensional space spanned by genomic single nucleotide polymorphism (SNP) vectors and study its properties in different gene-action scenarios. Two different kriging methods [“universal kriging” (UK) and “simple kriging” (SK)] are presented. As a novelty, we suggest use of the family of Matérn covariance functions to model the covariance structure of SNP vectors. A genomic best linear unbiased prediction (GBLUP) is applied as a reference method. The three approaches are compared in a whole-genome simulation study considering additive, additive-dominance, and epistatic gene-action models. Predictive performance is measured in terms of correlation between true and predicted GVs and average true GVs of the individuals ranked best by prediction. We show that UK outperforms GBLUP in the presence of dominance and epistatic effects. In a limiting case, it is shown that the genomic covariance structure proposed by VanRaden (2008) can be considered as a covariance function with corresponding quadratic variogram. We also prove theoretically that if a specific linear relationship exists between covariance matrices for two linear mixed models, the GVs resulting from BLUP are linked by a scaling factor. Finally, the relation of kriging to other models is discussed and further options for modeling the covariance structure, which might be more appropriate in the genomic context, are suggested. PMID:21515573
Implementation of optimal phase-covariant cloning machines
Sciarrino, Fabio; De Martini, Francesco
2007-07-15
The optimal phase-covariant quantum cloning machine (PQCM) broadcasts the information associated to an input qubit into a multiqubit system, exploiting a partial a priori knowledge of the input state. This additional a priori information leads to a higher fidelity than for the universal cloning. The present article first analyzes different innovative schemes to implement the 1{yields}3 PQCM. The method is then generalized to any 1{yields}M machine for an odd value of M by a theoretical approach based on the general angular momentum formalism. Finally different experimental schemes based either on linear or nonlinear methods and valid for single photon polarization encoded qubits are discussed.
Covariates of Sesame Street Viewing by Preschoolers.
ERIC Educational Resources Information Center
Spaner, Steven D.
A study was made of nine covariates as to their discriminating power between preschoolers who watch Sesame Street regularly and preschoolers who do not watch Sesame Street, Surveyed were 372 3-4 year old children on 9 variables. The nine variables were: race, socioeconomic status, number of siblings, child's birth order, maternal age, maternal…
Observed Score Linear Equating with Covariates
ERIC Educational Resources Information Center
Branberg, Kenny; Wiberg, Marie
2011-01-01
This paper examined observed score linear equating in two different data collection designs, the equivalent groups design and the nonequivalent groups design, when information from covariates (i.e., background variables correlated with the test scores) was included. The main purpose of the study was to examine the effect (i.e., bias, variance, and…
Invariance of covariances arises out of noise
NASA Astrophysics Data System (ADS)
Grytskyy, D.; Tetzlaff, T.; Diesmann, M.; Helias, M.
2013-01-01
Correlated neural activity is a known feature of the brain [1] and evidence increases that it is closely linked to information processing [2]. The temporal shape of covariances has early been related to synaptic interactions and to common input shared by pairs of neurons [3]. Recent theoretical work explains the small magnitude of covariances in inhibition dominated recurrent networks by active decorrelation [4, 5, 6]. For binary neurons the mean-field approach takes random fluctuations into account to accurately predict the average activity in such networks [7] and expressions for covariances follow from a master equation [8], both briefly reviewed here for completeness. In our recent work we have shown how to map different network models, including binary networks, onto linear dynamics [9]. Binary neurons with a strong non-linear Heaviside gain function are inaccessible to the classical treatment [8]. Here we show how random fluctuations generated by the network effectively linearize the system and implement a self-regulating mechanism, that renders population-averaged covariances independent of the interaction strength and keeps the system away from instability.
Covariant Photon Quantization in the SME
NASA Astrophysics Data System (ADS)
Colladay, D.
2014-01-01
The Gupta-Bleuler quantization procedure is applied to the SME photon sector. A direct application of the method to the massless case fails due to an unavoidable incompleteness in the polarization states. A mass term can be included into the photon lagrangian to rescue the quantization procedure and maintain covariance.
Economical phase-covariant cloning of qudits
Buscemi, Francesco; D'Ariano, Giacomo Mauro; Macchiavello, Chiara
2005-04-01
We derive the optimal N{yields}M phase-covariant quantum cloning for equatorial states in dimension d with M=kd+N, k integer. The cloning maps are optimal for both global and single-qudit fidelity. The map is achieved by an 'economical' cloning machine, which works without ancilla.
Gauge field theory of covariant strings
NASA Astrophysics Data System (ADS)
Kaku, Michio
1986-03-01
We present a gauge covariant second-quantized field theory of strings which is explicitly invariant under the gauge transformations generated by the Virasoro algebra. Unlike the old field theory strings [1] this new formulation is Lorentz covariant as well as gauge covariant under the continuous group Diff( S1) and its central extension. We derive the free action: L=Φ(X) †P[i∂ τ-(L 0-1)]PΦ(X) , in the same way that Feynman derived the Schrödinger equation from the path integral formalism. The action is manifestly invariant under the gauge transformation δΦ(X)= limit∑n=1∞ɛ -nL -nΦ(X) , where P is a projection operator which annihilates spurious states. We give three distinct formulations of this operator P to all orders, the first based on extracting the operator from the functional formulation of the Nambu-Goto action, and the second and third based on inverting the Shapovalov matrix on a Verma module. This gauge covariant formulation can be easily extended to the Green-Schwarz superstring [2,3]. One element application of these methods is to re-express the old Neveu-Schwarz-Ramond model as a field theory which is manifestly invariant under space-time supersymmetric transformations.
Nuclear moments in covariant density functional theory
NASA Astrophysics Data System (ADS)
Meng, J.; Zhao, P. W.; Zhang, S. Q.; Hu, J. N.; Li, J.
2014-05-01
Recent progresses on microscopic and self-consistent description of the nuclear moments in covariant density functional theory based on a point-coupling interaction are briefly reviewed. In particular, the electric quadrupole moments of Cd isotopes and the magnetic moments of Pb isotopes are discussed.
Hawking fluxes, back reaction and covariant anomalies
NASA Astrophysics Data System (ADS)
Kulkarni, Shailesh
2008-11-01
Starting from the chiral covariant effective action approach of Banerjee and Kulkarni (2008 Phys. Lett. B 659 827), we provide a derivation of the Hawking radiation from a charged black hole in the presence of gravitational back reaction. The modified expressions for charge and energy flux, due to the effect of one-loop back reaction are obtained.
General covariance, artificial gauge freedom and empirical equivalence
NASA Astrophysics Data System (ADS)
Pitts, James Brian
This dissertation updates the debate over the nontriviality of general covariance for Einstein's General Theory of Relativity (GTR) and considers particle physics in the debate over underdetermination and empirical equivalence. Both tasks are tied to the unexplored issue of artificial gauge freedom, a valuable form of descriptive redundancy. Whereas Einstein took general covariance to characterize GTR, Kretschmann thought it merely a formal feature that any theory could have. Anderson and Friedman analyzed substantive general covariance as the lack of absolute objects, fields the same in all models. Some extant counterexamples and a new one involving the electron spinor field are resolved. However, Geroch and Giulini diagnose an absolute object in GTR itself in the metric's volume element. One might instead analyze substantive general covariance as formal general covariance achieved without hiding preferred coordinates as scalar "clock fields," recalling Einstein's early views. Theories with no metric or multiple metrics make the age of the universe meaningless or ambiguous, respectively, so the ancient and medieval debate over the eternity of the world should be recast. Particle physics provides case studies for empirical equivalence. Proca's electromagnetism with some nonzero photon mass constitutes a family of rivals to Maxwell's theory. Whereas any Proca theory can be distinguished empirically from Maxwell's, the Proca family approaches Maxwell's for small masses, yielding permanent underdetermination with only approximate empirical equivalence. The weak nuclear force also displays a smooth massless limit classically, but not after quantization, recalling the instability of empirical equivalence under change of auxiliary hypotheses. The standard electroweak theory apparently permits a photon mass term and hence underdetermination, but possible further unification might not. The question of underdetermination regarding massive gravity is unresolved. Physicists
A novel algorithm for detecting multiple covariance and clustering of biological sequences.
Shen, Wei; Li, Yan
2016-01-01
Single genetic mutations are always followed by a set of compensatory mutations. Thus, multiple changes commonly occur in biological sequences and play crucial roles in maintaining conformational and functional stability. Although many methods are available to detect single mutations or covariant pairs, detecting non-synchronous multiple changes at different sites in sequences remains challenging. Here, we develop a novel algorithm, named Fastcov, to identify multiple correlated changes in biological sequences using an independent pair model followed by a tandem model of site-residue elements based on inter-restriction thinking. Fastcov performed exceptionally well at harvesting co-pairs and detecting multiple covariant patterns. By 10-fold cross-validation using datasets of different scales, the characteristic patterns successfully classified the sequences into target groups with an accuracy of greater than 98%. Moreover, we demonstrated that the multiple covariant patterns represent co-evolutionary modes corresponding to the phylogenetic tree, and provide a new understanding of protein structural stability. In contrast to other methods, Fastcov provides not only a reliable and effective approach to identify covariant pairs but also more powerful functions, including multiple covariance detection and sequence classification, that are most useful for studying the point and compensatory mutations caused by natural selection, drug induction, environmental pressure, etc. PMID:27451921
A novel algorithm for detecting multiple covariance and clustering of biological sequences
Shen, Wei; Li, Yan
2016-01-01
Single genetic mutations are always followed by a set of compensatory mutations. Thus, multiple changes commonly occur in biological sequences and play crucial roles in maintaining conformational and functional stability. Although many methods are available to detect single mutations or covariant pairs, detecting non-synchronous multiple changes at different sites in sequences remains challenging. Here, we develop a novel algorithm, named Fastcov, to identify multiple correlated changes in biological sequences using an independent pair model followed by a tandem model of site-residue elements based on inter-restriction thinking. Fastcov performed exceptionally well at harvesting co-pairs and detecting multiple covariant patterns. By 10-fold cross-validation using datasets of different scales, the characteristic patterns successfully classified the sequences into target groups with an accuracy of greater than 98%. Moreover, we demonstrated that the multiple covariant patterns represent co-evolutionary modes corresponding to the phylogenetic tree, and provide a new understanding of protein structural stability. In contrast to other methods, Fastcov provides not only a reliable and effective approach to identify covariant pairs but also more powerful functions, including multiple covariance detection and sequence classification, that are most useful for studying the point and compensatory mutations caused by natural selection, drug induction, environmental pressure, etc. PMID:27451921
Barbau-Piednoir, Elodie; De Keersmaecker, Sigrid C. J.; Wuyts, Véronique; Gau, Céline; Pirovano, Walter; Costessi, Adalberto; Philipp, Patrick
2015-01-01
This paper announces the genome sequence and annotation of the genetically modified (GM) Bacillus subtilis strain 2014-3557 overproducing riboflavin (vitamin B2). This GM-strain is unauthorized in the European Union. Nevertheless, it has been isolated from a lot of vitamin B2 (riboflavin) 80% feed grade imported to Europe from China. PMID:25858836
Covariance modeling in geodetic applications of collocation
NASA Astrophysics Data System (ADS)
Barzaghi, Riccardo; Cazzaniga, Noemi; De Gaetani, Carlo; Reguzzoni, Mirko
2014-05-01
Collocation method is widely applied in geodesy for estimating/interpolating gravity related functionals. The crucial problem of this approach is the correct modeling of the empirical covariance functions of the observations. Different methods for getting reliable covariance models have been proposed in the past by many authors. However, there are still problems in fitting the empirical values, particularly when different functionals of T are used and combined. Through suitable linear combinations of positive degree variances a model function that properly fits the empirical values can be obtained. This kind of condition is commonly handled by solver algorithms in linear programming problems. In this work the problem of modeling covariance functions has been dealt with an innovative method based on the simplex algorithm. This requires the definition of an objective function to be minimized (or maximized) where the unknown variables or their linear combinations are subject to some constraints. The non-standard use of the simplex method consists in defining constraints on model covariance function in order to obtain the best fit on the corresponding empirical values. Further constraints are applied so to have coherence with model degree variances to prevent possible solutions with no physical meaning. The fitting procedure is iterative and, in each iteration, constraints are strengthened until the best possible fit between model and empirical functions is reached. The results obtained during the test phase of this new methodology show remarkable improvements with respect to the software packages available until now. Numerical tests are also presented to check for the impact that improved covariance modeling has on the collocation estimate.
Renaud, Sabrina; Pantalacci, Sophie; Quéré, Jean-Pierre; Laudet, Vincent; Auffray, Jean-Christophe
2009-01-01
Morphological integration corresponds to interdependency between characters that can arise from several causes. Proximal causes of integration include that different phenotypic features may share common genetic sets and/or interact during their development. Ultimate causes may be the prolonged effect of selection favoring integration of functionally interacting characters, achieved by the molding of these proximal causes. Strong and direct interactions among successive teeth of a molar row are predicted by genetic and developmental evidences. Functional constraints related to occlusion, however, should have selected more strongly for a morphological integration of occluding teeth and a corresponding evolution of the underlying developmental and genetic pathways. To investigate how these predictions match the patterns of phenotypic integration, we studied the co-variation among the six molars of the murine molar row, focusing on two populations of house mice (Mus musculus domesticus) and wood mice (Apodemus sylvaticus). The size and shape of the three upper and lower molars were quantified and compared. Our results evidenced similar patterns in both species, size being more integrated than shape among all the teeth, and both size and shape co-varying strongly between adjacent teeth, but also between occluding teeth. Strong co-variation within each molar row is in agreement with developmental models showing a cascade influence of the first molar on the subsequent molars. In contrast, the strong co-variation between molars of the occluding tooth rows confirms that functional constraints molded patterns of integration and probably the underlying developmental pathways despite the low level of direct developmental interactions occurring among molar rows. These patterns of co-variation are furthermore conserved between the house mouse and the wood mouse that diverged >10 Ma, suggesting that they may constitute long-running constraints to the diversification of the murine
dos Reis, Matheus Costa; Pádua, José Maria Villela; Abreu, Guilherme Barbosa; Guedes, Fernando Lisboa; Balbi, Rodrigo Vieira; de Souza, João Cândido
2014-01-01
This study was carried out to obtain the estimates of genetic variance and covariance components related to intra- and interpopulation in the original populations (C0) and in the third cycle (C3) of reciprocal recurrent selection (RRS) which allows breeders to define the best breeding strategy. For that purpose, the half-sib progenies of intrapopulation (P11 and P22) and interpopulation (P12 and P21) from populations 1 and 2 derived from single-cross hybrids in the 0 and 3 cycles of the reciprocal recurrent selection program were used. The intra- and interpopulation progenies were evaluated in a 10 × 10 triple lattice design in two separate locations. The data for unhusked ear weight (ear weight without husk) and plant height were collected. All genetic variance and covariance components were estimated from the expected mean squares. The breakdown of additive variance into intrapopulation and interpopulation additive deviations (στ2) and the covariance between these and their intrapopulation additive effects (CovAτ) found predominance of the dominance effect for unhusked ear weight. Plant height for these components shows that the intrapopulation additive effect explains most of the variation. Estimates for intrapopulation and interpopulation additive genetic variances confirm that populations derived from single-cross hybrids have potential for recurrent selection programs. PMID:25009831
Das, Kiranmoy; Daniels, Michael J
2014-03-01
Estimation of the covariance structure for irregular sparse longitudinal data has been studied by many authors in recent years but typically using fully parametric specifications. In addition, when data are collected from several groups over time, it is known that assuming the same or completely different covariance matrices over groups can lead to loss of efficiency and/or bias. Nonparametric approaches have been proposed for estimating the covariance matrix for regular univariate longitudinal data by sharing information across the groups under study. For the irregular case, with longitudinal measurements that are bivariate or multivariate, modeling becomes more difficult. In this article, to model bivariate sparse longitudinal data from several groups, we propose a flexible covariance structure via a novel matrix stick-breaking process for the residual covariance structure and a Dirichlet process mixture of normals for the random effects. Simulation studies are performed to investigate the effectiveness of the proposed approach over more traditional approaches. We also analyze a subset of Framingham Heart Study data to examine how the blood pressure trajectories and covariance structures differ for the patients from different BMI groups (high, medium, and low) at baseline. PMID:24400941
Linear covariance analysis for gimbaled pointing systems
NASA Astrophysics Data System (ADS)
Christensen, Randall S.
Linear covariance analysis has been utilized in a wide variety of applications. Historically, the theory has made significant contributions to navigation system design and analysis. More recently, the theory has been extended to capture the combined effect of navigation errors and closed-loop control on the performance of the system. These advancements have made possible rapid analysis and comprehensive trade studies of complicated systems ranging from autonomous rendezvous to vehicle ascent trajectory analysis. Comprehensive trade studies are also needed in the area of gimbaled pointing systems where the information needs are different from previous applications. It is therefore the objective of this research to extend the capabilities of linear covariance theory to analyze the closed-loop navigation and control of a gimbaled pointing system. The extensions developed in this research include modifying the linear covariance equations to accommodate a wider variety of controllers. This enables the analysis of controllers common to gimbaled pointing systems, with internal states and associated dynamics as well as actuator command filtering and auxiliary controller measurements. The second extension is the extraction of power spectral density estimates from information available in linear covariance analysis. This information is especially important to gimbaled pointing systems where not just the variance but also the spectrum of the pointing error impacts the performance. The extended theory is applied to a model of a gimbaled pointing system which includes both flexible and rigid body elements as well as input disturbances, sensor errors, and actuator errors. The results of the analysis are validated by direct comparison to a Monte Carlo-based analysis approach. Once the developed linear covariance theory is validated, analysis techniques that are often prohibitory with Monte Carlo analysis are used to gain further insight into the system. These include the creation
Comparing G: multivariate analysis of genetic variation in multiple populations.
Aguirre, J D; Hine, E; McGuigan, K; Blows, M W
2014-01-01
The additive genetic variance-covariance matrix (G) summarizes the multivariate genetic relationships among a set of traits. The geometry of G describes the distribution of multivariate genetic variance, and generates genetic constraints that bias the direction of evolution. Determining if and how the multivariate genetic variance evolves has been limited by a number of analytical challenges in comparing G-matrices. Current methods for the comparison of G typically share several drawbacks: metrics that lack a direct relationship to evolutionary theory, the inability to be applied in conjunction with complex experimental designs, difficulties with determining statistical confidence in inferred differences and an inherently pair-wise focus. Here, we present a cohesive and general analytical framework for the comparative analysis of G that addresses these issues, and that incorporates and extends current methods with a strong geometrical basis. We describe the application of random skewers, common subspace analysis, the 4th-order genetic covariance tensor and the decomposition of the multivariate breeders equation, all within a Bayesian framework. We illustrate these methods using data from an artificial selection experiment on eight traits in Drosophila serrata, where a multi-generational pedigree was available to estimate G in each of six populations. One method, the tensor, elegantly captures all of the variation in genetic variance among populations, and allows the identification of the trait combinations that differ most in genetic variance. The tensor approach is likely to be the most generally applicable method to the comparison of G-matrices from any sampling or experimental design. PMID:23486079
Low-Fidelity Covariances: Neutron Cross Section Covariance Estimates for 387 Materials
The Low-fidelity Covariance Project (Low-Fi) was funded in FY07-08 by DOEÆs Nuclear Criticality Safety Program (NCSP). The project was a collaboration among ANL, BNL, LANL, and ORNL. The motivation for the Low-Fi project stemmed from an imbalance in supply and demand of covariance data. The interest in, and demand for, covariance data has been in a continual uptrend over the past few years. Requirements to understand application-dependent uncertainties in simulated quantities of interest have led to the development of sensitivity / uncertainty and data adjustment software such as TSUNAMI [1] at Oak Ridge. To take full advantage of the capabilities of TSUNAMI requires general availability of covariance data. However, the supply of covariance data has not been able to keep up with the demand. This fact is highlighted by the observation that the recent release of the much-heralded ENDF/B-VII.0 included covariance data for only 26 of the 393 neutron evaluations (which is, in fact, considerably less covariance data than was included in the final ENDF/B-VI release).[Copied from R.C. Little et al., "Low-Fidelity Covariance Project", Nuclear Data Sheets 109 (2008) 2828-2833] The Low-Fi covariance data are now available at the National Nuclear Data Center. They are separate from ENDF/B-VII.0 and the NNDC warns that this information is not approved by CSEWG. NNDC describes the contents of this collection as: "Covariance data are provided for radiative capture (or (n,ch.p.) for light nuclei), elastic scattering (or total for some actinides), inelastic scattering, (n,2n) reactions, fission and nubars over the energy range from 10(-5{super}) eV to 20 MeV. The library contains 387 files including almost all (383 out of 393) materials of the ENDF/B-VII.0. Absent are data for (7{super})Li, (232{super})Th, (233,235,238{super})U and (239{super})Pu as well as (223,224,225,226{super})Ra, while (nat{super})Zn is replaced by (64,66,67,68,70{super})Zn
Covariance and the hierarchy of frame bundles
NASA Technical Reports Server (NTRS)
Estabrook, Frank B.
1987-01-01
This is an essay on the general concept of covariance, and its connection with the structure of the nested set of higher frame bundles over a differentiable manifold. Examples of covariant geometric objects include not only linear tensor fields, densities and forms, but affinity fields, sectors and sector forms, higher order frame fields, etc., often having nonlinear transformation rules and Lie derivatives. The intrinsic, or invariant, sets of forms that arise on frame bundles satisfy the graded Cartan-Maurer structure equations of an infinite Lie algebra. Reduction of these gives invariant structure equations for Lie pseudogroups, and for G-structures of various orders. Some new results are introduced for prolongation of structure equations, and for treatment of Riemannian geometry with higher-order moving frames. The use of invariant form equations for nonlinear field physics is implicitly advocated.
On covariance structure in noisy, big data
NASA Astrophysics Data System (ADS)
Paffenroth, Randy C.; Nong, Ryan; Du Toit, Philip C.
2013-09-01
Herein we describe theory and algorithms for detecting covariance structures in large, noisy data sets. Our work uses ideas from matrix completion and robust principal component analysis to detect the presence of low-rank covariance matrices, even when the data is noisy, distorted by large corruptions, and only partially observed. In fact, the ability to handle partial observations combined with ideas from randomized algorithms for matrix decomposition enables us to produce asymptotically fast algorithms. Herein we will provide numerical demonstrations of the methods and their convergence properties. While such methods have applicability to many problems, including mathematical finance, crime analysis, and other large-scale sensor fusion problems, our inspiration arises from applying these methods in the context of cyber network intrusion detection.
Covariance Spectroscopy Applied to Nuclear Radiation Detection
Trainham, R., Tinsley, J., Keegan, R., Quam, W.
2011-09-01
Covariance spectroscopy is a method of processing second order moments of data to obtain information that is usually absent from average spectra. In nuclear radiation detection it represents a generalization of nuclear coincidence techniques. Correlations and fluctuations in data encode valuable information about radiation sources, transport media, and detection systems. Gaining access to the extra information can help to untangle complicated spectra, uncover overlapping peaks, accelerate source identification, and even sense directionality. Correlations existing at the source level are particularly valuable since many radioactive isotopes emit correlated gammas and neutrons. Correlations also arise from interactions within detector systems, and from scattering in the environment. In particular, correlations from Compton scattering and pair production within a detector array can be usefully exploited in scenarios where direct measurement of source correlations would be unfeasible. We present a covariance analysis of a few experimental data sets to illustrate the utility of the concept.
Covariant quantum mechanics applied to noncommutative geometry
NASA Astrophysics Data System (ADS)
Astuti, Valerio
2015-08-01
We here report a result obtained in collaboration with Giovanni Amelino-Camelia, first shown in the paper [1]. Applying the manifestly covariant formalism of quantum mechanics to the much studied Snyder spacetime [2] we show how it is trivial in every physical observables, this meaning that every measure in this spacetime gives the same results that would be obtained in the flat Minkowski spacetime.
Economical phase-covariant cloning with multiclones
NASA Astrophysics Data System (ADS)
Zhang, Wen-Hai; Ye, Liu
2009-09-01
This paper presents a very simple method to derive the explicit transformations of the optimal economical 1 to M phase-covariant cloning. The fidelity of clones reaches the theoretic bound [D'Ariano G M and Macchiavello C 2003 Phys. Rev. A 67 042306]. The derived transformations cover the previous contributions [Delgado Y, Lamata L et al., 2007 Phys. Rev. Lett. 98 150502] in which M must be odd.
Partial covariance mapping techniques at FELs
NASA Astrophysics Data System (ADS)
Frasinski, Leszek
2014-05-01
The development of free-electron lasers (FELs) is driven by the desire to access the structure and chemical dynamics of biomolecules with atomic resolution. Short, intense FEL pulses have the potential to record x-ray diffraction images before the molecular structure is destroyed by radiation damage. However, even during the shortest, few-femtosecond pulses currently available, there are some significant changes induced by massive ionisation and onset of Coulomb explosion. To interpret the diffraction images it is vital to gain insight into the electronic and nuclear dynamics during multiple core and valence ionisations that compete with Auger cascades. This paper focuses on a technique that is capable to probe these processes. The covariance mapping technique is well suited to the high intensity and low repetition rate of FEL pulses. While the multitude of charges ejected at each pulse overwhelm conventional coincidence methods, an improved technique of partial covariance mapping can cope with hundreds of photoelectrons or photoions detected at each FEL shot. The technique, however, often reveals spurious, uninteresting correlations that spoil the maps. This work will discuss the strengths and limitations of various forms of covariance mapping techniques. Quantitative information extracted from the maps will be linked to theoretical modelling of ionisation and fragmentation paths. Special attention will be given to critical experimental parameters, such as counting rate, FEL intensity fluctuations, vacuum impurities or detector efficiency and nonlinearities. Methods of assessing and optimising signal-to-noise ratio will be described. Emphasis will be put on possible future developments such as multidimensional covariance mapping, compensation for various experimental instabilities and improvements in the detector response. This work has been supported the EPSRC, UK (grants EP/F021232/1 and EP/I032517/1).
Using Covariance Analysis to Assess Pointing Performance
NASA Technical Reports Server (NTRS)
Bayard, David; Kang, Bryan
2009-01-01
A Pointing Covariance Analysis Tool (PCAT) has been developed for evaluating the expected performance of the pointing control system for NASA s Space Interferometry Mission (SIM). The SIM pointing control system is very complex, consisting of multiple feedback and feedforward loops, and operating with multiple latencies and data rates. The SIM pointing problem is particularly challenging due to the effects of thermomechanical drifts in concert with the long camera exposures needed to image dim stars. Other pointing error sources include sensor noises, mechanical vibrations, and errors in the feedforward signals. PCAT models the effects of finite camera exposures and all other error sources using linear system elements. This allows the pointing analysis to be performed using linear covariance analysis. PCAT propagates the error covariance using a Lyapunov equation associated with time-varying discrete and continuous-time system matrices. Unlike Monte Carlo analysis, which could involve thousands of computational runs for a single assessment, the PCAT analysis performs the same assessment in a single run. This capability facilitates the analysis of parametric studies, design trades, and "what-if" scenarios for quickly evaluating and optimizing the control system architecture and design.
Covariance tracking: architecture optimizations for embedded systems
NASA Astrophysics Data System (ADS)
Romero, Andrés; Lacassagne, Lionel; Gouiffès, Michèle; Zahraee, Ali Hassan
2014-12-01
Covariance matching techniques have recently grown in interest due to their good performances for object retrieval, detection, and tracking. By mixing color and texture information in a compact representation, it can be applied to various kinds of objects (textured or not, rigid or not). Unfortunately, the original version requires heavy computations and is difficult to execute in real time on embedded systems. This article presents a review on different versions of the algorithm and its various applications; our aim is to describe the most crucial challenges and particularities that appeared when implementing and optimizing the covariance matching algorithm on a variety of desktop processors and on low-power processors suitable for embedded systems. An application of texture classification is used to compare different versions of the region descriptor. Then a comprehensive study is made to reach a higher level of performance on multi-core CPU architectures by comparing different ways to structure the information, using single instruction, multiple data (SIMD) instructions and advanced loop transformations. The execution time is reduced significantly on two dual-core CPU architectures for embedded computing: ARM Cortex-A9 and Cortex-A15 and Intel Penryn-M U9300 and Haswell-M 4650U. According to our experiments on covariance tracking, it is possible to reach a speedup greater than ×2 on both ARM and Intel architectures, when compared to the original algorithm, leading to real-time execution.
Shrinkage covariance matrix approach for microarray data
NASA Astrophysics Data System (ADS)
Karjanto, Suryaefiza; Aripin, Rasimah
2013-04-01
Microarray technology was developed for the purpose of monitoring the expression levels of thousands of genes. A microarray data set typically consists of tens of thousands of genes (variables) from just dozens of samples due to various constraints including the high cost of producing microarray chips. As a result, the widely used standard covariance estimator is not appropriate for this purpose. One such technique is the Hotelling's T2 statistic which is a multivariate test statistic for comparing means between two groups. It requires that the number of observations (n) exceeds the number of genes (p) in the set but in microarray studies it is common that n < p. This leads to a biased estimate of the covariance matrix. In this study, the Hotelling's T2 statistic with the shrinkage approach is proposed to estimate the covariance matrix for testing differential gene expression. The performance of this approach is then compared with other commonly used multivariate tests using a widely analysed diabetes data set as illustrations. The results across the methods are consistent, implying that this approach provides an alternative to existing techniques.
Development of covariance capabilities in EMPIRE code
Herman,M.; Pigni, M.T.; Oblozinsky, P.; Mughabghab, S.F.; Mattoon, C.M.; Capote, R.; Cho, Young-Sik; Trkov, A.
2008-06-24
The nuclear reaction code EMPIRE has been extended to provide evaluation capabilities for neutron cross section covariances in the thermal, resolved resonance, unresolved resonance and fast neutron regions. The Atlas of Neutron Resonances by Mughabghab is used as a primary source of information on uncertainties at low energies. Care is taken to ensure consistency among the resonance parameter uncertainties and those for thermal cross sections. The resulting resonance parameter covariances are formatted in the ENDF-6 File 32. In the fast neutron range our methodology is based on model calculations with the code EMPIRE combined with experimental data through several available approaches. The model-based covariances can be obtained using deterministic (Kalman) or stochastic (Monte Carlo) propagation of model parameter uncertainties. We show that these two procedures yield comparable results. The Kalman filter and/or the generalized least square fitting procedures are employed to incorporate experimental information. We compare the two approaches analyzing results for the major reaction channels on {sup 89}Y. We also discuss a long-standing issue of unreasonably low uncertainties and link it to the rigidity of the model.
Development of Covariance Capabilities in EMPIRE Code
Herman, M. Pigni, M.T.; Oblozinsky, P.; Mughabghab, S.F.; Mattoon, C.M.; Capote, R.; Cho, Young-Sik; Trkov, A.
2008-12-15
The nuclear reaction code EMPIRE has been extended to provide evaluation capabilities for neutron cross section covariances in the thermal, resolved resonance, unresolved resonance and fast neutron regions. The Atlas of Neutron Resonances by Mughabghab is used as a primary source of information on uncertainties at low energies. Care is taken to ensure consistency among the resonance parameter uncertainties and those for thermal cross sections. The resulting resonance parameter covariances are formatted in the ENDF-6 File 32. In the fast neutron range our methodology is based on model calculations with the code EMPIRE combined with experimental data through several available approaches. The model-based covariances can be obtained using deterministic (Kalman) or stochastic (Monte Carlo) propagation of model parameter uncertainties. We show that these two procedures yield comparable results. The Kalman filter and/or the generalized least square fitting procedures are employed to incorporate experimental information. We compare the two approaches analyzing results for the major reaction channels on {sup 89}Y. We also discuss a long-standing issue of unreasonably low uncertainties and link it to the rigidity of the model.
Retrospective likelihood-based methods for analyzing case-cohort genetic association studies.
Shen, Yuanyuan; Cai, Tianxi; Chen, Yu; Yang, Ying; Chen, Jinbo
2015-12-01
The case cohort (CCH) design is a cost-effective design for assessing genetic susceptibility with time-to-event data especially when the event rate is low. In this work, we propose a powerful pseudo-score test for assessing the association between a single nucleotide polymorphism (SNP) and the event time under the CCH design. The pseudo-score is derived from a pseudo-likelihood which is an estimated retrospective likelihood that treats the SNP genotype as the dependent variable and time-to-event outcome and other covariates as independent variables. It exploits the fact that the genetic variable is often distributed independent of covariates or only related to a low-dimensional subset. Estimates of hazard ratio parameters for association can be obtained by maximizing the pseudo-likelihood. A unique advantage of our method is that it allows the censoring distribution to depend on covariates that are only measured for the CCH sample while not requiring the knowledge of follow-up or covariate information on subjects not selected into the CCH sample. In addition to these flexibilities, the proposed method has high relative efficiency compared with commonly used alternative approaches. We study large sample properties of this method and assess its finite sample performance using both simulated and real data examples. PMID:26177343
Graff, Mariaelisa; Ngwa, Julius S.; Workalemahu, Tsegaselassie; Homuth, Georg; Schipf, Sabine; Teumer, Alexander; Völzke, Henry; Wallaschofski, Henri; Abecasis, Goncalo R.; Edward, Lakatta; Francesco, Cucca; Sanna, Serena; Scheet, Paul; Schlessinger, David; Sidore, Carlo; Xiao, Xiangjun; Wang, Zhaoming; Chanock, Stephen J.; Jacobs, Kevin B.; Hayes, Richard B.; Hu, Frank; Van Dam, Rob M.; Crout, Richard J.; Marazita, Mary L.; Shaffer, John R; Atwood, Larry D.; Fox, Caroline S.; Heard-Costa, Nancy L.; White, Charles; Choh, Audrey C.; Czerwinski, Stefan A.; Demerath, Ellen W.; Dyer, Thomas D.; Towne, Bradford; Amin, Najaf; Oostra, Ben A.; Van Duijn, Cornelia M.; Zillikens, M. Carola; Esko, Tõnu; Nelis, Mari; Nikopensius, Tit; Metspalu, Andres; Strachan, David P.; Monda, Keri; Qi, Lu; North, Kari E.; Cupples, L. Adrienne; Gordon-Larsen, Penny; Berndt, Sonja I.
2013-01-01
Genetic loci for body mass index (BMI) in adolescence and young adulthood, a period of high risk for weight gain, are understudied, yet may yield important insight into the etiology of obesity and early intervention. To identify novel genetic loci and examine the influence of known loci on BMI during this critical time period in late adolescence and early adulthood, we performed a two-stage meta-analysis using 14 genome-wide association studies in populations of European ancestry with data on BMI between ages 16 and 25 in up to 29 880 individuals. We identified seven independent loci (P < 5.0 × 10−8) near FTO (P = 3.72 × 10−23), TMEM18 (P = 3.24 × 10−17), MC4R (P = 4.41 × 10−17), TNNI3K (P = 4.32 × 10−11), SEC16B (P = 6.24 × 10−9), GNPDA2 (P = 1.11 × 10−8) and POMC (P = 4.94 × 10−8) as well as a potential secondary signal at the POMC locus (rs2118404, P = 2.4 × 10−5 after conditioning on the established single-nucleotide polymorphism at this locus) in adolescents and young adults. To evaluate the impact of the established genetic loci on BMI at these young ages, we examined differences between the effect sizes of 32 published BMI loci in European adult populations (aged 18–90) and those observed in our adolescent and young adult meta-analysis. Four loci (near PRKD1, TNNI3K, SEC16B and CADM2) had larger effects and one locus (near SH2B1) had a smaller effect on BMI during adolescence and young adulthood compared with older adults (P < 0.05). These results suggest that genetic loci for BMI can vary in their effects across the life course, underlying the importance of evaluating BMI at different ages. PMID:23669352
ANALYSIS OF COVARIANCE WITH SPATIALLY CORRELATED SECONDARY VARIABLES
Technology Transfer Automated Retrieval System (TEKTRAN)
Data sets which contain measurements on a spatially referenced response and covariate are analyzed using either co-kriging or spatial analysis of covariance. While co-kriging accounts for the correlation structure of the covariate, it is purely a predictive tool. Alternatively, spatial analysis of c...
Covariate Selection in Propensity Scores Using Outcome Proxies
ERIC Educational Resources Information Center
Kelcey, Ben
2011-01-01
This study examined the practical problem of covariate selection in propensity scores (PSs) given a predetermined set of covariates. Because the bias reduction capacity of a confounding covariate is proportional to the concurrent relationships it has with the outcome and treatment, particular focus is set on how we might approximate…
Eliciting Systematic Rule Use in Covariation Judgment [the Early Years].
ERIC Educational Resources Information Center
Shaklee, Harriet; Paszek, Donald
Related research suggests that children may show some simple understanding of event covariations by the early elementary school years. The present experiments use a rule analysis methodology to investigate covariation judgments of children in this age range. In Experiment 1, children in second, third and fourth grade judged covariations on 12…
Covariant Perturbation Expansion of Off-Diagonal Heat Kernel
NASA Astrophysics Data System (ADS)
Gou, Yu-Zi; Li, Wen-Du; Zhang, Ping; Dai, Wu-Sheng
2016-07-01
Covariant perturbation expansion is an important method in quantum field theory. In this paper an expansion up to arbitrary order for off-diagonal heat kernels in flat space based on the covariant perturbation expansion is given. In literature, only diagonal heat kernels are calculated based on the covariant perturbation expansion.
Earth Observation System Flight Dynamics System Covariance Realism
NASA Technical Reports Server (NTRS)
Zaidi, Waqar H.; Tracewell, David
2016-01-01
This presentation applies a covariance realism technique to the National Aeronautics and Space Administration (NASA) Earth Observation System (EOS) Aqua and Aura spacecraft based on inferential statistics. The technique consists of three parts: collection calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics.
Hidden Covariation Detection Produces Faster, Not Slower, Social Judgments
ERIC Educational Resources Information Center
Barker, Lynne A.; Andrade, Jackie
2006-01-01
In P. Lewicki's (1986b) demonstration of hidden covariation detection (HCD), responses of participants were slower to faces that corresponded with a covariation encountered previously than to faces with novel covariations. This slowing contrasts with the typical finding that priming leads to faster responding and suggests that HCD is a unique type…
Chaste, Pauline; Klei, Lambertus; Sanders, Stephan J.; Murtha, Michael T.; Hus, Vanessa; Lowe, Jennifer K.; Willsey, A. Jeremy; Moreno-De-Luca, Daniel; Yu, Timothy W.; Fombonne, Eric; Geschwind, Daniel; Grice, Dorothy E.; Ledbetter, David H.; Lord, Catherine; Mane, Shrikant M.; Martin, Christa Lese; Martin, Donna M.; Morrow, Eric M.; Walsh, Christopher A.; Sutcliffe, James S.; State, Matthew W.; Devlin, Bernie; Cook, Edwin H.; Kim, Soo-Jeong
2013-01-01
BACKGROUND Brain development follows a different trajectory in children with Autism Spectrum Disorders (ASD) than in typically developing children. A proxy for neurodevelopment could be head circumference (HC), but studies assessing HC and its clinical correlates in ASD have been inconsistent. This study investigates HC and clinical correlates in the Simons Simplex Collection cohort. METHODS We used a mixed linear model to estimate effects of covariates and the deviation from the expected HC given parental HC (genetic deviation). After excluding individuals with incomplete data, 7225 individuals in 1891 families remained for analysis. We examined the relationship between HC/genetic deviation of HC and clinical parameters. RESULTS Gender, age, height, weight, genetic ancestry and ASD status were significant predictors of HC (estimate of the ASD effect=0.2cm). HC was approximately normally distributed in probands and unaffected relatives, with only a few outliers. Genetic deviation of HC was also normally distributed, consistent with a random sampling of parental genes. Whereas larger HC than expected was associated with ASD symptom severity and regression, IQ decreased with the absolute value of the genetic deviation of HC. CONCLUSIONS Measured against expected values derived from covariates of ASD subjects, statistical outliers for HC were uncommon. HC is a strongly heritable trait and population norms for HC would be far more accurate if covariates including genetic ancestry, height and age were taken into account. The association of diminishing IQ with absolute deviation from predicted HC values suggests HC could reflect subtle underlying brain development and warrants further investigation. PMID:23746936
Covariant balance laws in continua with microstructure
NASA Astrophysics Data System (ADS)
Yavari, Arash; Marsden, Jerrold E.
2009-02-01
The purpose of this paper is to extend the Green-Naghdi-Rivlin balance of energy method to continua with microstructure. The key idea is to replace the group of Galilean transformations with the group of diffeomorphisms of the ambient space. A key advantage is that one obtains in a natural way all the needed balance laws on both the macro and micro levels along with two Doyle-Erickson formulas. We model a structured continuum as a triplet of Riemannian manifolds: a material manifold, the ambient space manifold of material particles and a director field manifold. The Green-Naghdi-Rivlin theorem and its extensions for structured continua are critically reviewed. We show that when the ambient space is Euclidean and when the microstructure manifold is the tangent space of the ambient space manifold, postulating a single balance of energy law and its invariance under time-dependent isometries of the ambient space, one obtains conservation of mass, balances of linear and angular momenta but not a separate balance of linear momentum. We develop a covariant elasticity theory for structured continua by postulating that energy balance is invariant under time-dependent spatial diffeomorphisms of the ambient space, which in this case is the product of two Riemannian manifolds. We then introduce two types of constrained continua in which microstructure manifold is linked to the reference and ambient space manifolds. In the case when at every material point, the microstructure manifold is the tangent space of the ambient space manifold at the image of the material point, we show that the assumption of covariance leads to balances of linear and angular momenta with contributions from both forces and micro-forces along with two Doyle-Ericksen formulas. We show that generalized covariance leads to two balances of linear momentum and a single coupled balance of angular momentum. Using this theory, we covariantly obtain the balance laws for two specific examples, namely elastic
Covariance Between Genotypic Effects and its Use for Genomic Inference in Half-Sib Families
Wittenburg, Dörte; Teuscher, Friedrich; Klosa, Jan; Reinsch, Norbert
2016-01-01
In livestock, current statistical approaches utilize extensive molecular data, e.g., single nucleotide polymorphisms (SNPs), to improve the genetic evaluation of individuals. The number of model parameters increases with the number of SNPs, so the multicollinearity between covariates can affect the results obtained using whole genome regression methods. In this study, dependencies between SNPs due to linkage and linkage disequilibrium among the chromosome segments were explicitly considered in methods used to estimate the effects of SNPs. The population structure affects the extent of such dependencies, so the covariance among SNP genotypes was derived for half-sib families, which are typical in livestock populations. Conditional on the SNP haplotypes of the common parent (sire), the theoretical covariance was determined using the haplotype frequencies of the population from which the individual parent (dam) was derived. The resulting covariance matrix was included in a statistical model for a trait of interest, and this covariance matrix was then used to specify prior assumptions for SNP effects in a Bayesian framework. The approach was applied to one family in simulated scenarios (few and many quantitative trait loci) and using semireal data obtained from dairy cattle to identify genome segments that affect performance traits, as well as to investigate the impact on predictive ability. Compared with a method that does not explicitly consider any of the relationship among predictor variables, the accuracy of genetic value prediction was improved by 10–22%. The results show that the inclusion of dependence is particularly important for genomic inference based on small sample sizes. PMID:27402363
Nonparametric Covariate-Adjusted Association Tests Based on the Generalized Kendall’s Tau*
Zhu, Wensheng; Jiang, Yuan; Zhang, Heping
2012-01-01
Identifying the risk factors for comorbidity is important in psychiatric research. Empirically, studies have shown that testing multiple, correlated traits simultaneously is more powerful than testing a single trait at a time in association analysis. Furthermore, for complex diseases, especially mental illnesses and behavioral disorders, the traits are often recorded in different scales such as dichotomous, ordinal and quantitative. In the absence of covariates, nonparametric association tests have been developed for multiple complex traits to study comorbidity. However, genetic studies generally contain measurements of some covariates that may affect the relationship between the risk factors of major interest (such as genes) and the outcomes. While it is relatively easy to adjust these covariates in a parametric model for quantitative traits, it is challenging for multiple complex traits with possibly different scales. In this article, we propose a nonparametric test for multiple complex traits that can adjust for covariate effects. The test aims to achieve an optimal scheme of adjustment by using a maximum statistic calculated from multiple adjusted test statistics. We derive the asymptotic null distribution of the maximum test statistic, and also propose a resampling approach, both of which can be used to assess the significance of our test. Simulations are conducted to compare the type I error and power of the nonparametric adjusted test to the unadjusted test and other existing adjusted tests. The empirical results suggest that our proposed test increases the power through adjustment for covariates when there exist environmental effects, and is more robust to model misspecifications than some existing parametric adjusted tests. We further demonstrate the advantage of our test by analyzing a data set on genetics of alcoholism. PMID:22745516
Quantum energy inequalities and local covariance II: categorical formulation
NASA Astrophysics Data System (ADS)
Fewster, Christopher J.
2007-11-01
We formulate quantum energy inequalities (QEIs) in the framework of locally covariant quantum field theory developed by Brunetti, Fredenhagen and Verch, which is based on notions taken from category theory. This leads to a new viewpoint on the QEIs, and also to the identification of a new structural property of locally covariant quantum field theory, which we call local physical equivalence. Covariant formulations of the numerical range and spectrum of locally covariant fields are given and investigated, and a new algebra of fields is identified, in which fields are treated independently of their realisation on particular spacetimes and manifestly covariant versions of the functional calculus may be formulated.
Jiang, Shan; Chen, Bingshu; Tu, Dongshengn
2016-07-20
The investigation of the treatment-covariate interaction is of considerable interest in the design and analysis of clinical trials. With potentially censored data observed, non-parametric and semi-parametric estimates and associated confidence intervals are proposed in this paper to quantify the interactions between the treatment and a binary covariate. In addition, comparison of interactions between the treatment and two covariates are also considered. The proposed approaches are evaluated and compared by Monte Carlo simulations and applied to a real data set from a cancer clinical trial. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26887976
Autism-Specific Covariation in Perceptual Performances: “g” or “p” Factor?
Meilleur, Andrée-Anne S.; Berthiaume, Claude; Bertone, Armando; Mottron, Laurent
2014-01-01
Background Autistic perception is characterized by atypical and sometimes exceptional performance in several low- (e.g., discrimination) and mid-level (e.g., pattern matching) tasks in both visual and auditory domains. A factor that specifically affects perceptive abilities in autistic individuals should manifest as an autism-specific association between perceptual tasks. The first purpose of this study was to explore how perceptual performances are associated within or across processing levels and/or modalities. The second purpose was to determine if general intelligence, the major factor that accounts for covariation in task performances in non-autistic individuals, equally controls perceptual abilities in autistic individuals. Methods We asked 46 autistic individuals and 46 typically developing controls to perform four tasks measuring low- or mid-level visual or auditory processing. Intelligence was measured with the Wechsler's Intelligence Scale (FSIQ) and Raven Progressive Matrices (RPM). We conducted linear regression models to compare task performances between groups and patterns of covariation between tasks. The addition of either Wechsler's FSIQ or RPM in the regression models controlled for the effects of intelligence. Results In typically developing individuals, most perceptual tasks were associated with intelligence measured either by RPM or Wechsler FSIQ. The residual covariation between unimodal tasks, i.e. covariation not explained by intelligence, could be explained by a modality-specific factor. In the autistic group, residual covariation revealed the presence of a plurimodal factor specific to autism. Conclusions Autistic individuals show exceptional performance in some perceptual tasks. Here, we demonstrate the existence of specific, plurimodal covariation that does not dependent on general intelligence (or “g” factor). Instead, this residual covariation is accounted for by a common perceptual process (or “p” factor), which may drive
Dominance Genetic Variance for Traits Under Directional Selection in Drosophila serrata
Sztepanacz, Jacqueline L.; Blows, Mark W.
2015-01-01
In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait–fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. PMID:25783700
Dominance genetic variance for traits under directional selection in Drosophila serrata.
Sztepanacz, Jacqueline L; Blows, Mark W
2015-05-01
In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait-fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. PMID:25783700
Sesana, R C; Bignardi, A B; Borquis, R R A; El Faro, L; Baldi, F; Albuquerque, L G; Tonhati, H
2010-10-01
The objective of this work was to estimate covariance functions for additive genetic and permanent environmental effects and, subsequently, to obtain genetic parameters for buffalo's test-day milk production using random regression models on Legendre polynomials (LPs). A total of 17 935 test-day milk yield (TDMY) from 1433 first lactations of Murrah buffaloes, calving from 1985 to 2005 and belonging to 12 herds located in São Paulo state, Brazil, were analysed. Contemporary groups (CGs) were defined by herd, year and month of milk test. Residual variances were modelled through variance functions, from second to fourth order and also by a step function with 1, 4, 6, 22 and 42 classes. The model of analyses included the fixed effect of CGs, number of milking, age of cow at calving as a covariable (linear and quadratic) and the mean trend of the population. As random effects were included the additive genetic and permanent environmental effects. The additive genetic and permanent environmental random effects were modelled by LP of days in milk from quadratic to seventh degree polynomial functions. The model with additive genetic and animal permanent environmental effects adjusted by quintic and sixth order LP, respectively, and residual variance modelled through a step function with six classes was the most adequate model to describe the covariance structure of the data. Heritability estimates decreased from 0.44 (first week) to 0.18 (fourth week). Unexpected negative genetic correlation estimates were obtained between TDMY records at first weeks with records from middle to the end of lactation, being the values varied from -0.07 (second with eighth week) to -0.34 (1st with 42nd week). TDMY heritability estimates were moderate in the course of the lactation, suggesting that this trait could be applied as selection criteria in milking buffaloes. PMID:20831561
Genetic control over the resting brain
Glahn, D. C.; Winkler, A. M.; Kochunov, P.; Almasy, L.; Duggirala, R.; Carless, M. A.; Curran, J. C.; Olvera, R. L.; Laird, A. R.; Smith, S. M.; Beckmann, C. F.; Fox, P. T.; Blangero, J.
2010-01-01
The default-mode network, a coherent resting-state brain network, is thought to characterize basal neural activity. Aberrant default-mode connectivity has been reported in a host of neurological and psychiatric illnesses and in persons at genetic risk for such illnesses. Whereas the neurophysiologic mechanisms that regulate default-mode connectivity are unclear, there is growing evidence that genetic factors play a role. In this report, we estimate the importance of genetic effects on the default-mode network by examining covariation patterns in functional connectivity among 333 individuals from 29 randomly selected extended pedigrees. Heritability for default-mode functional connectivity was 0.424 ± 0.17 (P = 0.0046). Although neuroanatomic variation in this network was also heritable, the genetic factors that influence default-mode functional connectivity and gray-matter density seem to be distinct, suggesting that unique genes influence the structure and function of the network. In contrast, significant genetic correlations between regions within the network provide evidence that the same genetic factors contribute to variation in functional connectivity throughout the default mode. Specifically, the left parahippocampal region was genetically correlated with all other network regions. In addition, the posterior cingulate/precuneus region, medial prefrontal cortex, and right cerebellum seem to form a subnetwork. Default-mode functional connectivity is influenced by genetic factors that cannot be attributed to anatomic variation or a single region within the network. By establishing the heritability of default-mode functional connectivity, this experiment provides the obligatory evidence required before these measures can be considered as endophenotypes for psychiatric or neurological illnesses or to identify genes influencing intrinsic brain function. PMID:20133824
The fermionic covariant prolongation structure of the super generalized Hirota equation
NASA Astrophysics Data System (ADS)
Yan, Zhaowen; Yao, Shaokui; Zhang, Chunhong; Gegenhasi
2016-07-01
The integrability of a super generalized Hirota equation (GHE) is investigated by means of the fermionic covariant prolongation structure theory. We construct the su(2/1) × R(λ) prolongation structure for the super GHE and derive the corresponding Lax representation and the Bäcklund transformation. In addition, a solution of the super integrable equation is presented.
Linear Covariance Analysis and Epoch State Estimators
NASA Technical Reports Server (NTRS)
Markley, F. Landis; Carpenter, J. Russell
2012-01-01
This paper extends in two directions the results of prior work on generalized linear covariance analysis of both batch least-squares and sequential estimators. The first is an improved treatment of process noise in the batch, or epoch state, estimator with an epoch time that may be later than some or all of the measurements in the batch. The second is to account for process noise in specifying the gains in the epoch state estimator. We establish the conditions under which the latter estimator is equivalent to the Kalman filter.
Linear Covariance Analysis and Epoch State Estimators
NASA Technical Reports Server (NTRS)
Markley, F. Landis; Carpenter, J. Russell
2014-01-01
This paper extends in two directions the results of prior work on generalized linear covariance analysis of both batch least-squares and sequential estimators. The first is an improved treatment of process noise in the batch, or epoch state, estimator with an epoch time that may be later than some or all of the measurements in the batch. The second is to account for process noise in specifying the gains in the epoch state estimator. We establish the conditions under which the latter estimator is equivalent to the Kalman filter.
Covariant harmonic oscillators and coupled harmonic oscillators
NASA Technical Reports Server (NTRS)
Han, Daesoo; Kim, Young S.; Noz, Marilyn E.
1995-01-01
It is shown that the system of two coupled harmonic oscillators shares the basic symmetry properties with the covariant harmonic oscillator formalism which provides a concise description of the basic features of relativistic hadronic features observed in high-energy laboratories. It is shown also that the coupled oscillator system has the SL(4,r) symmetry in classical mechanics, while the present formulation of quantum mechanics can accommodate only the Sp(4,r) portion of the SL(4,r) symmetry. The possible role of the SL(4,r) symmetry in quantum mechanics is discussed.
Inferring Meta-covariates in Classification
NASA Astrophysics Data System (ADS)
Harris, Keith; McMillan, Lisa; Girolami, Mark
This paper develops an alternative method for gene selection that combines model based clustering and binary classification. By averaging the covariates within the clusters obtained from model based clustering, we define “meta-covariates” and use them to build a probit regression model, thereby selecting clusters of similarly behaving genes, aiding interpretation. This simultaneous learning task is accomplished by an EM algorithm that optimises a single likelihood function which rewards good performance at both classification and clustering. We explore the performance of our methodology on a well known leukaemia dataset and use the Gene Ontology to interpret our results.
Cosmology of a Covariant Galileon Field
NASA Astrophysics Data System (ADS)
de Felice, Antonio; Tsujikawa, Shinji
2010-09-01
We study the cosmology of a covariant scalar field respecting a Galilean symmetry in flat space-time. We show the existence of a tracker solution that finally approaches a de Sitter fixed point responsible for cosmic acceleration today. The viable region of model parameters is clarified by deriving conditions under which ghosts and Laplacian instabilities of scalar and tensor perturbations are absent. The field equation of state exhibits a peculiar phantomlike behavior along the tracker, which allows a possibility to observationally distinguish the Galileon gravity from the cold dark matter model with a cosmological constant.
Shape covariation between the craniofacial complex and first molars in humans
Polychronis, Georgios; Halazonetis, Demetrios J
2014-01-01
The occurrence of mutual genetic loci in morphogenesis of the face and teeth implies shape covariation between these structures. However, teeth finalize their shape at an early age, whereas the face grows and is subjected to environmental influences for a prolonged period; it is therefore conceivable that covariation might modulate with age. Here we investigate the extent of this covariation in humans by measuring the 3D shape of the occlusal surface of the permanent first molars and the shape of the craniofacial complex from lateral radiographs, at two maturations stages. A sample of Greek subjects was divided into two groups (110 adult, 110 prepubertal) with equally distributed gender. The occlusal surfaces of the right first molars were 3D scanned from dental casts; 265 and 274 landmarks (including surface and curve semilandmarks) were digitized on the maxillary and mandibular molars, respectively. The corresponding lateral cephalometric radiographs were digitized with 71 landmarks. Geometric morphometric methods were used to assess shape variation and covariation. The vertical dimension of the craniofacial complex was the main parameter of shape variation, followed by anteroposterior deviations. The male craniofacial complex was larger (4.0–5.7%) and was characterized by a prominent chin and clockwise rotation of the cranial base (adult group only). Allometry was weak and statistically significant only when examined for the sample as a whole (percent variance explained: 2.1%, P = 0.0002). Covariation was statistically significant only between the lower first molar and the craniofacial complex (RV = 14.05%, P = 0.0099, and RV = 12.31%, P = 0.0162, for the prepubertal and adult groups, respectively). Subtle age-related covariation differences were noted, indicating that environmental factors may influence the pattern and strength of covariation. However, the main pattern was similar in both groups: a class III skeletal pattern (relative maxillary retrusion and
Fully Bayesian inference under ignorable missingness in the presence of auxiliary covariates
Daniels, M.J.; Wang, C.; Marcus, B.H.
2014-01-01
In order to make a missing at random (MAR) or ignorability assumption realistic, auxiliary covariates are often required. However, the auxiliary covariates are not desired in the model for inference. Typical multiple imputation approaches do not assume that the imputation model marginalizes to the inference model. This has been termed ‘uncongenial’ (Meng, 1994). In order to make the two models congenial (or compatible), we would rather not assume a parametric model for the marginal distribution of the auxiliary covariates, but we typically do not have enough data to estimate the joint distribution well non-parametrically. In addition, when the imputation model uses a non-linear link function (e.g., the logistic link for a binary response), the marginalization over the auxiliary covariates to derive the inference model typically results in a difficult to interpret form for effect of covariates. In this article, we propose a fully Bayesian approach to ensure that the models are compatible for incomplete longitudinal data by embedding an interpretable inference model within an imputation model and that also addresses the two complications described above. We evaluate the approach via simulations and implement it on a recent clinical trial. PMID:24571539
Disruption of structural covariance networks for language in autism is modulated by verbal ability.
Sharda, Megha; Khundrakpam, Budhachandra S; Evans, Alan C; Singh, Nandini C
2016-03-01
The presence of widespread speech and language deficits is a core feature of autism spectrum disorders (ASD). These impairments have often been attributed to altered connections between brain regions. Recent developments in anatomical correlation-based approaches to map structural covariance offer an effective way of studying such connections in vivo. In this study, we employed such a structural covariance network (SCN)-based approach to investigate the integrity of anatomical networks in fronto-temporal brain regions of twenty children with ASD compared to an age and gender-matched control group of twenty-two children. Our findings reflected large-scale disruption of inter and intrahemispheric covariance in left frontal SCNs in the ASD group compared to controls, but no differences in right fronto-temporal SCNs. Interhemispheric covariance in left-seeded networks was further found to be modulated by verbal ability of the participants irrespective of autism diagnosis, suggesting that language function might be related to the strength of interhemispheric structural covariance between frontal regions. Additionally, regional cortical thickening was observed in right frontal and left posterior regions, which was predicted by decreasing symptom severity and increasing verbal ability in ASD. These findings unify reports of regional differences in cortical morphology in ASD. They also suggest that reduced left hemisphere asymmetry and increased frontal growth may not only reflect neurodevelopmental aberrations but also compensatory mechanisms. PMID:25445842
Klimentidis, Y C; Miller, G F; Shriver, M D
2009-01-01
Previous studies have shown a relationship between health-related phenotypes and the degree of African, European, or Native American genetic admixture, indicating that there may be a genetic component to these phenotypes. However, these relationships may be driven to a large extent by the environmental differences that co-vary with admixture differences between and within groups. In this study, we examine the relationship between genetic admixture and two phenotypic measurements that are potentially related to health: body mass index (BMI) and percent body fat (PBF). In addition to admixture proportions, we attempt to assess the influence of some environmental covariates by examining how the phenotypes vary with self-reported household income, education of parents, and physical activity level. Genetic, anthropometric, and environmental data were collected from 170 self-reported Hispanic and Native American university students in Albuquerque, NM. We examine the relationships between genetic admixture, phenotype, and environment in both the full sample, as well as in Hispanics and Native Americans separately. Among Hispanics, we find no significant relationship between genetic admixture and body composition. Among Native Americans, despite a small sample size, we find a statistically significant, negative relationship between European genetic admixture and PBF and BMI, after adjusting for other predictor variables. We compare our findings to previous research, and discuss their implications for understanding health disparities within and between ethnic groups. PMID:19214998
Hard, J J; Bradshaw, W E; Holzapfel, C M
1993-09-01
We measured the additive genetic variance within populations and the composite additive, dominance, and epistatic effects contributing to differentiation of photoperiodic response between two southern (ancestral) and each of four progressively more northern (derived) populations of the pitcher-plant mosquito, Wyeomyia smithii. Critical photoperiod and its additive genetic variance but not its heritability increased with latitude. Directional selection on critical photoperiod during the northward divergence of W. smithii has therefore not eroded the additive genetic variance underlying this trait. Joint scaling tests of crosses between populations showed that epistatic effects, especially additive x additive and dominance x dominance interactions, overwhelm composite additive and dominance effects on critical photoperiod. The presence of substantial epistasis suggests that multiple founder events during the northward divergence of W. smithii may have been responsible for the release of progressively greater additive genetic variance in derived populations, despite directional and stabilizing selection to reduce it. If epistasis makes a similar contribution to the genetic differentiation of populations in other species, then current models of adaptive evolution that consider only additive genetic variation and covariation within populations may be of limited value in predicting how natural populations differentiate in life history. PMID:19425986
Comparative Analysis of Evapotranspiration Using Eddy Covariance
NASA Astrophysics Data System (ADS)
BAE, H.; Ji, H.; Lee, B.; Nam, K.; Jang, B.; Lee, C.; Jung, H.
2013-12-01
The eddy covariance method has been widely used to quantify evapotranspiration. However, independent measurements of energy components such as latent heat flux, sensible heat flux often lead to under-measurements, this is commonly known as a lack of closure of the surface energy balance. In response to this methodological problem, this study is addressed specifically to correction of the latent and heat sensible fluxes. The energy components observed in agricultural and grassland from January 2013 were measured using the eddy covariance method. As a result of the comparison of the available energy (Rn-G) with the sum of the latent and sensible heat fluxes, R-Squared values were 0.72 in the agricultural land, 0.78 in the grassland, indicating that the latent and sensible heat fluxes were under-measured. The obtained latent and sensible heat fluxes were then modified using the Bowen-ratio closure method. After this correction process, the values of the sum of the latent and sensible heat fluxes have increased by 39.7 percent in the agricultural land, 32.2 percent in the grassland respectively. Evapotranspiration will be calculated with both the unmodified and modified latent heat flux values, the results will be then thoroughly compared. The results will be finally verified by comparison with evapotranspiration obtained from energy balance based model.
Noisy covariance matrices and portfolio optimization
NASA Astrophysics Data System (ADS)
Pafka, S.; Kondor, I.
2002-05-01
According to recent findings [#!bouchaud!#,#!stanley!#], empirical covariance matrices deduced from financial return series contain such a high amount of noise that, apart from a few large eigenvalues and the corresponding eigenvectors, their structure can essentially be regarded as random. In [#!bouchaud!#], e.g., it is reported that about 94% of the spectrum of these matrices can be fitted by that of a random matrix drawn from an appropriately chosen ensemble. In view of the fundamental role of covariance matrices in the theory of portfolio optimization as well as in industry-wide risk management practices, we analyze the possible implications of this effect. Simulation experiments with matrices having a structure such as described in [#!bouchaud!#,#!stanley!#] lead us to the conclusion that in the context of the classical portfolio problem (minimizing the portfolio variance under linear constraints) noise has relatively little effect. To leading order the solutions are determined by the stable, large eigenvalues, and the displacement of the solution (measured in variance) due to noise is rather small: depending on the size of the portfolio and on the length of the time series, it is of the order of 5 to 15%. The picture is completely different, however, if we attempt to minimize the variance under non-linear constraints, like those that arise e.g. in the problem of margin accounts or in international capital adequacy regulation. In these problems the presence of noise leads to a serious instability and a high degree of degeneracy of the solutions.
Estimating the power spectrum covariance matrix with fewer mock samples
NASA Astrophysics Data System (ADS)
Pearson, David W.; Samushia, Lado
2016-03-01
The covariance matrices of power-spectrum (P(k)) measurements from galaxy surveys are difficult to compute theoretically. The current best practice is to estimate covariance matrices by computing a sample covariance of a large number of mock catalogues. The next generation of galaxy surveys will require thousands of large volume mocks to determine the covariance matrices to desired accuracy. The errors in the inverse covariance matrix are larger and scale with the number of P(k) bins, making the problem even more acute. We develop a method of estimating covariance matrices using a theoretically justified, few-parameter model, calibrated with mock catalogues. Using a set of 600 BOSS DR11 mock catalogues, we show that a seven parameter model is sufficient to fit the covariance matrix of BOSS DR11 P(k) measurements. The covariance computed with this method is better than the sample covariance at any number of mocks and only ˜100 mocks are required for it to fully converge and the inverse covariance matrix converges at the same rate. This method should work equally well for the next generation of galaxy surveys, although a demand for higher accuracy may require adding extra parameters to the fitting function.
A Class of Population Covariance Matrices in the Bootstrap Approach to Covariance Structure Analysis
ERIC Educational Resources Information Center
Yuan, Ke-Hai; Hayashi, Kentaro; Yanagihara, Hirokazu
2007-01-01
Model evaluation in covariance structure analysis is critical before the results can be trusted. Due to finite sample sizes and unknown distributions of real data, existing conclusions regarding a particular statistic may not be applicable in practice. The bootstrap procedure automatically takes care of the unknown distribution and, for a given…
Evaluation the initial estimators using deterministic minimum covariance determinant algorithm
NASA Astrophysics Data System (ADS)
Alrawashdeh, Mufda Jameel; Sabri, Shamsul Rijal Muhammad; Ismail, Mohd Tahir
2014-07-01
The aim of the study is to examine five initial estimators introduced by Hubert et al. [1] with five additional new initial estimators by using the Deterministic Minimum Covariance Determinant algorithm, DetMCD. The objective of the DetMCD is to robustify the location and scatter matrix parameters. Since these parameters are highly influenced by the presence of outliers, the DetMCD is a newly highly robust algorithm, where it is constructed to overcome the outlier's problem. DetMCD precedes the non-random subsets, which computes a small number of deterministic initial estimators and followed by concentration steps. Here, we are going to compare the DetMCD algorithm based on two groups of estimators - one with original five Huberts' estimators and the other five new estimators. The determinant values of these estimators are observed to evaluate the performance via several cases.
Orbit Determination Covariance Analysis for the Europa Clipper Mission
NASA Technical Reports Server (NTRS)
Ionasescu, Rodica; Martin-Mur, Tomas; Valerino, Powtawche; Criddle, Kevin; Buffington, Brent; McElrath, Timothy
2014-01-01
A new Jovian satellite tour is proposed by NASA, which would include numerous flybys of the moon Europa, and would explore its potential habitability by characterizing the existence of any water within and beneath Europa's ice shell. This paper describes the results of a covariance study that was undertaken on a sample tour to assess the navigational challenges and capabilities of such a mission from an orbit determination (OD) point of view, and to help establish a delta V budget for the maneuvers needed to keep the spacecraft on the reference trajectory. Additional parametric variations from the baseline case were also investigated. The success of the Europa Clipper mission will depend on the science measurements that it will enable. Meeting the requirements of the instruments onboard the spacecraft is an integral part of this analysis.
Backreaction of cosmological perturbations in covariant macroscopic gravity
NASA Astrophysics Data System (ADS)
Paranjape, Aseem
2008-09-01
The problem of corrections to Einstein’s equations arising from averaging of inhomogeneities (backreaction) in the cosmological context has gained considerable attention recently. We present results of analyzing cosmological perturbation theory in the framework of Zalaletdinov’s fully covariant macroscopic gravity. We show that this framework can be adapted to the setting of cosmological perturbations in a manner which is free from gauge related ambiguities. We derive expressions for the backreaction which can be readily applied in any situation (not necessarily restricted to the linear perturbations considered here) where the metric can be brought to the perturbed Friedmann-Lemaître-Robertson-Walker form. In particular, these expressions can be employed in toy models studying nonlinear structure formation, and possibly also in N-body simulations. Additionally, we present results of example calculations which show that the backreaction remains negligible well into the matter dominated era.
Spencer, Chris C.A.; Plagnol, Vincent; Strange, Amy; Gardner, Michelle; Paisan-Ruiz, Coro; Band, Gavin; Barker, Roger A.; Bellenguez, Celine; Bhatia, Kailash; Blackburn, Hannah; Blackwell, Jennie M.; Bramon, Elvira; Brown, Martin A.; Brown, Matthew A.; Burn, David; Casas, Juan-Pablo; Chinnery, Patrick F.; Clarke, Carl E.; Corvin, Aiden; Craddock, Nicholas; Deloukas, Panos; Edkins, Sarah; Evans, Jonathan; Freeman, Colin; Gray, Emma; Hardy, John; Hudson, Gavin; Hunt, Sarah; Jankowski, Janusz; Langford, Cordelia; Lees, Andrew J.; Markus, Hugh S.; Mathew, Christopher G.; McCarthy, Mark I.; Morrison, Karen E.; Palmer, Colin N.A.; Pearson, Justin P.; Peltonen, Leena; Pirinen, Matti; Plomin, Robert; Potter, Simon; Rautanen, Anna; Sawcer, Stephen J.; Su, Zhan; Trembath, Richard C.; Viswanathan, Ananth C.; Williams, Nigel W.; Morris, Huw R.; Donnelly, Peter; Wood, Nicholas W.
2011-01-01
We performed a genome-wide association study (GWAS) in 1705 Parkinson's disease (PD) UK patients and 5175 UK controls, the largest sample size so far for a PD GWAS. Replication was attempted in an additional cohort of 1039 French PD cases and 1984 controls for the 27 regions showing the strongest evidence of association (P< 10−4). We replicated published associations in the 4q22/SNCA and 17q21/MAPT chromosome regions (P< 10−10) and found evidence for an additional independent association in 4q22/SNCA. A detailed analysis of the haplotype structure at 17q21 showed that there are three separate risk groups within this region. We found weak but consistent evidence of association for common variants located in three previously published associated regions (4p15/BST1, 4p16/GAK and 1q32/PARK16). We found no support for the previously reported SNP association in 12q12/LRRK2. We also found an association of the two SNPs in 4q22/SNCA with the age of onset of the disease. PMID:21044948
AFCI-2.0 Library of Neutron Cross Section Covariances
Herman, M.; Herman,M.; Oblozinsky,P.; Mattoon,C.; Pigni,M.; Hoblit,S.; Mughabghab,S.F.; Sonzogni,A.; Talou,P.; Chadwick,M.B.; Hale.G.M.; Kahler,A.C.; Kawano,T.; Little,R.C.; Young,P.G.
2011-06-26
Neutron cross section covariance library has been under development by BNL-LANL collaborative effort over the last three years. The primary purpose of the library is to provide covariances for the Advanced Fuel Cycle Initiative (AFCI) data adjustment project, which is focusing on the needs of fast advanced burner reactors. The covariances refer to central values given in the 2006 release of the U.S. neutron evaluated library ENDF/B-VII. The preliminary version (AFCI-2.0beta) has been completed in October 2010 and made available to the users for comments. In the final 2.0 release, covariances for a few materials were updated, in particular new LANL evaluations for {sup 238,240}Pu and {sup 241}Am were adopted. BNL was responsible for covariances for structural materials and fission products, management of the library and coordination of the work, while LANL was in charge of covariances for light nuclei and for actinides.
Covariates of intravenous paracetamol pharmacokinetics in adults
2014-01-01
Background Pharmacokinetic estimates for intravenous paracetamol in individual adult cohorts are different to a certain extent, and understanding the covariates of these differences may guide dose individualization. In order to assess covariate effects of intravenous paracetamol disposition in adults, pharmacokinetic data on discrete studies were pooled. Methods This pooled analysis was based on 7 studies, resulting in 2755 time-concentration observations in 189 adults (mean age 46 SD 23 years; weight 73 SD 13 kg) given intravenous paracetamol. The effects of size, age, pregnancy and other clinical settings (intensive care, high dependency, orthopaedic or abdominal surgery) on clearance and volume of distribution were explored using non-linear mixed effects models. Results Paracetamol disposition was best described using normal fat mass (NFM) with allometric scaling as a size descriptor. A three-compartment linear disposition model revealed that the population parameter estimates (between subject variability,%) were central volume (V1) 24.6 (55.5%) L/70 kg with peripheral volumes of distribution V2 23.1 (49.6%) L/70 kg and V3 30.6 (78.9%) L/70 kg. Clearance (CL) was 16.7 (24.6%) L/h/70 kg and inter-compartment clearances were Q2 67.3 (25.7%) L/h/70 kg and Q3 2.04 (71.3%) L/h/70 kg. Clearance and V2 decreased only slightly with age. Sex differences in clearance were minor and of no significance. Clearance, relative to median values, was increased during pregnancy (FPREG = 1.14) and decreased during abdominal surgery (FABDCL = 0.715). Patients undergoing orthopaedic surgery had a reduced V2 (FORTHOV = 0.649), while those in intensive care had increased V2 (FICV = 1.51). Conclusions Size and age are important covariates for paracetamol pharmacokinetics explaining approximately 40% of clearance and V2 variability. Dose individualization in adult subpopulations would achieve little benefit in the scenarios explored. PMID:25342929
Flux Partitioning by Isotopic Eddy Covariance
NASA Astrophysics Data System (ADS)
Wehr, R.; Munger, J. W.; Nelson, D. D.; McManus, J. B.; Zahniser, M. S.; Wofsy, S. C.; Saleska, S. R.
2011-12-01
Net ecosystem-atmosphere exchange of CO2 is routinely measured by eddy covariance at sites around the world, but studies of ecosystem processes are more interested in the gross photosynthetic and respiratory fluxes that comprise the net flux. The standard method of partitioning the net flux into these components has been to extrapolate nighttime respiration into daytime based on a relationship between nighttime respiration, temperature, and sometimes moisture. However, such relationships generally account for only a small portion of the variation in nighttime respiration, and the assumption that they can predict respiration throughout the day is dubious. A promising alternate method, known as isotopic flux partitioning, works by identifying the stable isotopic signatures of photosynthesis and respiration in the CO2 flux. We have used this method to partition the net flux at Harvard Forest, MA, based on eddy covariance measurements of the net 12CO2 and 13CO2 fluxes (as well as measurements of the sensible and latent heat fluxes and other meteorological variables). The CO2 isotopologues were measured at 4 Hz by an Aerodyne quantum cascade laser spectrometer with a δ13C precision of 0.4 % in 0.25 sec and 0.02 % in 100 sec. In the absence of such high-frequency, high-precision isotopic measurements, past attempts at isotopic flux partitioning have combined isotopic flask measurements with high-frequency (total) CO2 measurements to estimate the isoflux (the EC/flask approach). Others have used a conditional flask sampling approach called hyperbolic relaxed eddy accumulation (HREA). We 'sampled' our data according to each of these approaches, for comparison, and found disagreement in the calculated fluxes of ~10% for the EC/flask approach, and ~30% for HREA, at midday. To our knowledge, this is the first example of flux partitioning by isotopic eddy covariance. Wider use of this method, enabled by a new generation of laser spectrometers, promises to open a new window
Covariant entropy bound and loop quantum cosmology
Ashtekar, Abhay; Wilson-Ewing, Edward
2008-09-15
We examine Bousso's covariant entropy bound conjecture in the context of radiation filled, spatially flat, Friedmann-Robertson-Walker models. The bound is violated near the big bang. However, the hope has been that quantum gravity effects would intervene and protect it. Loop quantum cosmology provides a near ideal setting for investigating this issue. For, on the one hand, quantum geometry effects resolve the singularity and, on the other hand, the wave function is sharply peaked at a quantum corrected but smooth geometry, which can supply the structure needed to test the bound. We find that the bound is respected. We suggest that the bound need not be an essential ingredient for a quantum gravity theory but may emerge from it under suitable circumstances.
Covariant Lyapunov analysis of chaotic Kolmogorov flows.
Inubushi, Masanobu; Kobayashi, Miki U; Takehiro, Shin-ichi; Yamada, Michio
2012-01-01
Hyperbolicity is an important concept in dynamical system theory; however, we know little about the hyperbolicity of concrete physical systems including fluid motions governed by the Navier-Stokes equations. Here, we study numerically the hyperbolicity of the Navier-Stokes equation on a two-dimensional torus (Kolmogorov flows) using the method of covariant Lyapunov vectors developed by Ginelli et al. [Phys. Rev. Lett. 99, 130601 (2007)]. We calculate the angle between the local stable and unstable manifolds along an orbit of chaotic solution to evaluate the hyperbolicity. We find that the attractor of chaotic Kolmogorov flows is hyperbolic at small Reynolds numbers, but that smaller angles between the local stable and unstable manifolds are observed at larger Reynolds numbers, and the attractor appears to be nonhyperbolic at a certain Reynolds numbers. Also, we observed some relations between these hyperbolic properties and physical properties such as time correlation of the vorticity and the energy dissipation rate. PMID:22400681
Generation of phase-covariant quantum cloning
Karimipour, V.; Rezakhani, A.T.
2002-11-01
It is known that in phase-covariant quantum cloning, the equatorial states on the Bloch sphere can be cloned with a fidelity higher than the optimal bound established for universal quantum cloning. We generalize this concept to include other states on the Bloch sphere with a definite z component of spin. It is shown that once we know the z component, we can always clone a state with a fidelity higher than the universal value and that of equatorial states. We also make a detailed study of the entanglement properties of the output copies and show that the equatorial states are the only states that give rise to a separable density matrix for the outputs.
EMPIRE ULTIMATE EXPANSION: RESONANCES AND COVARIANCES.
HERMAN,M.; MUGHABGHAB, S.F.; OBLOZINSKY, P.; ROCHMAN, D.; PIGNI, M.T.; KAWANO, T.; CAPOTE, R.; ZERKIN, V.; TRKOV, A.; SIN, M.; CARSON, B.V.; WIENKE, H. CHO, Y.-S.
2007-04-22
The EMPIRE code system is being extended to cover the resolved and unresolved resonance region employing proven methodology used for the production of new evaluations in the recent Atlas of Neutron Resonances. Another directions of Empire expansion are uncertainties and correlations among them. These include covariances for cross sections as well as for model parameters. In this presentation we concentrate on the KALMAN method that has been applied in EMPIRE to the fast neutron range as well as to the resonance region. We also summarize role of the EMPIRE code in the ENDF/B-VII.0 development. Finally, large scale calculations and their impact on nuclear model parameters are discussed along with the exciting perspectives offered by the parallel supercomputing.
Covariant chronogeometry and extreme distances: Elementary particles
Segal, I. E.; Jakobsen, H. P.; Ørsted, B.; Paneitz, S. M.; Speh, B.
1981-01-01
We study a variant of elementary particle theory in which Minkowski space, M0, is replaced by a natural alternative, the unique four-dimensional manifold ¯M with comparable properties of causality and symmetry. Free particles are considered to be associated (i) with positive-energy representations in bundles of prescribed spin over ¯M of the group of causality-preserving transformations on ¯M (or its mass-conserving subgroup) and (ii) with corresponding wave equations. In this study these bundles, representations, and equations are detailed, and some of their basic features are developed in the cases of spins 0 and ½. Preliminaries to a general study are included; issues of covariance, unitarity, and positivity of the energy are treated; appropriate quantum numbers are indicated; and possible physical applications are discussed. PMID:16593075
Covariant generalization of cosmological perturbation theory
Enqvist, Kari; Hoegdahl, Janne; Nurmi, Sami; Vernizzi, Filippo
2007-01-15
We present an approach to cosmological perturbations based on a covariant perturbative expansion between two worldlines in the real inhomogeneous universe. As an application, at an arbitrary order we define an exact scalar quantity which describes the inhomogeneities in the number of e-folds on uniform density hypersurfaces and which is conserved on all scales for a barotropic ideal fluid. We derive a compact form for its conservation equation at all orders and assign it a simple physical interpretation. To make a comparison with the standard perturbation theory, we develop a method to construct gauge-invariant quantities in a coordinate system at arbitrary order, which we apply to derive the form of the nth order perturbation in the number of e-folds on uniform density hypersurfaces and its exact evolution equation. On large scales, this provides the gauge-invariant expression for the curvature perturbation on uniform density hypersurfaces and its evolution equation at any order.
Conformal killing tensors and covariant Hamiltonian dynamics
Cariglia, M.; Gibbons, G. W.; Holten, J.-W. van; Horvathy, P. A.; Zhang, P.-M.
2014-12-15
A covariant algorithm for deriving the conserved quantities for natural Hamiltonian systems is combined with the non-relativistic framework of Eisenhart, and of Duval, in which the classical trajectories arise as geodesics in a higher dimensional space-time, realized by Brinkmann manifolds. Conserved quantities which are polynomial in the momenta can be built using time-dependent conformal Killing tensors with flux. The latter are associated with terms proportional to the Hamiltonian in the lower dimensional theory and with spectrum generating algebras for higher dimensional quantities of order 1 and 2 in the momenta. Illustrations of the general theory include the Runge-Lenz vector for planetary motion with a time-dependent gravitational constant G(t), motion in a time-dependent electromagnetic field of a certain form, quantum dots, the Hénon-Heiles and Holt systems, respectively, providing us with Killing tensors of rank that ranges from one to six.
Covariant non-commutative space-time
NASA Astrophysics Data System (ADS)
Heckman, Jonathan J.; Verlinde, Herman
2015-05-01
We introduce a covariant non-commutative deformation of 3 + 1-dimensional conformal field theory. The deformation introduces a short-distance scale ℓp, and thus breaks scale invariance, but preserves all space-time isometries. The non-commutative algebra is defined on space-times with non-zero constant curvature, i.e. dS4 or AdS4. The construction makes essential use of the representation of CFT tensor operators as polynomials in an auxiliary polarization tensor. The polarization tensor takes active part in the non-commutative algebra, which for dS4 takes the form of so (5, 1), while for AdS4 it assembles into so (4, 2). The structure of the non-commutative correlation functions hints that the deformed theory contains gravitational interactions and a Regge-like trajectory of higher spin excitations.
A covariance analysis algorithm for interconnected systems
NASA Technical Reports Server (NTRS)
Cheng, Victor H. L.; Curley, Robert D.; Lin, Ching-An
1987-01-01
A covariance analysis algorithm for propagation of signal statistics in arbitrarily interconnected nonlinear systems is presented which is applied to six-degree-of-freedom systems. The algorithm uses statistical linearization theory to linearize the nonlinear subsystems, and the resulting linearized subsystems are considered in the original interconnection framework for propagation of the signal statistics. Some nonlinearities commonly encountered in six-degree-of-freedom space-vehicle models are referred to in order to illustrate the limitations of this method, along with problems not encountered in standard deterministic simulation analysis. Moreover, the performance of the algorithm shall be numerically exhibited by comparing results using such techniques to Monte Carlo analysis results, both applied to a simple two-dimensional space-intercept problem.
A covariant treatment of cosmic parallax
Räsänen, Syksy
2014-03-01
The Gaia satellite will soon probe parallax on cosmological distances. Using the covariant formalism and considering the angle between a pair of sources, we find parallax for both spacelike and timelike separation between observation points. Our analysis includes both intrinsic parallax and parallax due to observer motion. We propose a consistency condition that tests the FRW metric using the parallax distance and the angular diameter distance. This test is purely kinematic and relies only on geometrical optics, it is independent of matter content and its relation to the spacetime geometry. We study perturbations around the FRW model, and find that they should be taken into account when analysing observations to determine the parallax distance.
Performance of internal covariance estimators for cosmic shear correlation functions
Friedrich, O.; Seitz, S.; Eifler, T. F.; Gruen, D.
2015-12-31
Data re-sampling methods such as the delete-one jackknife are a common tool for estimating the covariance of large scale structure probes. In this paper we investigate the concepts of internal covariance estimation in the context of cosmic shear two-point statistics. We demonstrate how to use log-normal simulations of the convergence field and the corresponding shear field to carry out realistic tests of internal covariance estimators and find that most estimators such as jackknife or sub-sample covariance can reach a satisfactory compromise between bias and variance of the estimated covariance. In a forecast for the complete, 5-year DES survey we show that internally estimated covariance matrices can provide a large fraction of the true uncertainties on cosmological parameters in a 2D cosmic shear analysis. The volume inside contours of constant likelihood in the $\\Omega_m$-$\\sigma_8$ plane as measured with internally estimated covariance matrices is on average $\\gtrsim 85\\%$ of the volume derived from the true covariance matrix. The uncertainty on the parameter combination $\\Sigma_8 \\sim \\sigma_8 \\Omega_m^{0.5}$ derived from internally estimated covariances is $\\sim 90\\%$ of the true uncertainty.
Performance of internal covariance estimators for cosmic shear correlation functions
Friedrich, O.; Seitz, S.; Eifler, T. F.; Gruen, D.
2015-12-31
Data re-sampling methods such as the delete-one jackknife are a common tool for estimating the covariance of large scale structure probes. In this paper we investigate the concepts of internal covariance estimation in the context of cosmic shear two-point statistics. We demonstrate how to use log-normal simulations of the convergence field and the corresponding shear field to carry out realistic tests of internal covariance estimators and find that most estimators such as jackknife or sub-sample covariance can reach a satisfactory compromise between bias and variance of the estimated covariance. In a forecast for the complete, 5-year DES survey we show that internally estimated covariance matrices can provide a large fraction of the true uncertainties on cosmological parameters in a 2D cosmic shear analysis. The volume inside contours of constant likelihood in themore » $$\\Omega_m$$-$$\\sigma_8$$ plane as measured with internally estimated covariance matrices is on average $$\\gtrsim 85\\%$$ of the volume derived from the true covariance matrix. The uncertainty on the parameter combination $$\\Sigma_8 \\sim \\sigma_8 \\Omega_m^{0.5}$$ derived from internally estimated covariances is $$\\sim 90\\%$$ of the true uncertainty.« less
A Product Partition Model With Regression on Covariates
Müller, Peter; Quintana, Fernando; Rosner, Gary L.
2011-01-01
We propose a probability model for random partitions in the presence of covariates. In other words, we develop a model-based clustering algorithm that exploits available covariates. The motivating application is predicting time to progression for patients in a breast cancer trial. We proceed by reporting a weighted average of the responses of clusters of earlier patients. The weights should be determined by the similarity of the new patient’s covariate with the covariates of patients in each cluster. We achieve the desired inference by defining a random partition model that includes a regression on covariates. Patients with similar covariates are a priori more likely to be clustered together. Posterior predictive inference in this model formalizes the desired prediction. We build on product partition models (PPM). We define an extension of the PPM to include a regression on covariates by including in the cohesion function a new factor that increases the probability of experimental units with similar covariates to be included in the same cluster. We discuss implementations suitable for any combination of continuous, categorical, count, and ordinal covariates. An implementation of the proposed model as R-package is available for download. PMID:21566678
2014-01-01
Background Several methods are available for the detection of covarying positions from a multiple sequence alignment (MSA). If the MSA contains a large number of sequences, information about the proximities between residues derived from covariation maps can be sufficient to predict a protein fold. However, in many cases the structure is already known, and information on the covarying positions can be valuable to understand the protein mechanism and dynamic properties. Results In this study we have sought to determine whether a multivariate (multidimensional) extension of traditional mutual information (MI) can be an additional tool to study covariation. The performance of two multidimensional MI (mdMI) methods, designed to remove the effect of ternary/quaternary interdependencies, was tested with a set of 9 MSAs each containing <400 sequences, and was shown to be comparable to that of the newest methods based on maximum entropy/pseudolikelyhood statistical models of protein sequences. However, while all the methods tested detected a similar number of covarying pairs among the residues separated by < 8 Å in the reference X-ray structures, there was on average less than 65% overlap between the top scoring pairs detected by methods that are based on different principles. Conclusions Given the large variety of structure and evolutionary history of different proteins it is possible that a single best method to detect covariation in all proteins does not exist, and that for each protein family the best information can be derived by merging/comparing results obtained with different methods. This approach may be particularly valuable in those cases in which the size of the MSA is small or the quality of the alignment is low, leading to significant differences in the pairs detected by different methods. PMID:24886131
PRELIMINARY CROSS SECTION AND NU-BAR COVARIANCES FOR WPEC SUBGROUP 26
ROCHMAN,D.
2007-01-31
We report preliminary cross section covariances developed for the WPEC Subgroup 26 for 45 out of 52 requested materials. The covariances were produced in 15- and 187-group representations as follows: (1) 36 isotopes ({sup 16}O, {sup 19}F, {sup 23}Na, {sup 27}Al, {sup 28}Si, {sup 52}Cr, {sup 56,56}Fe, {sup 58}Ni, {sup 90,91,92,94}Zr, {sup 166,167,168,170}Er, {sup 206,207,208}Pb, {sup 209}Bi, {sup 233,234,236}U, {sup 237}Np, {sup 238,240,241,242}Pu, {sup 241,242m,243}Am, {sup 242,243,244,245}Cm) were evaluated using the BNL-LANL methodology. For the thermal region and the resolved and unresolved resonance regions, the methodology has been based on the Atlas-Kalman approach, in the fast neutron region the Empire-Kalman method has been used; (2) 6 isotopes ({sup 155,156,157,158,160}Gd and {sup 232}Th) were taken from ENDF/B-VII.0; and (3) 3 isotopes ({sup 1}H, {sup 238}U and {sup 239}Pu) were taken from JENDL-3.3. For 6 light nuclei ({sup 4}He, {sup 6,7}Li, {sup 9}Be, {sup 10}B, {sup 12}C), only partial cross section covariance results were obtained, additional work is needed and they do not report the results here. Likewise, the cross section covariances for {sup 235}U, which they recommend to take from JENDL-3.3, will be included once the multigroup processing is successfully completed. Covariances for the average number of neutrons per fission, total {nu}-bar, are provided for 10 actinides identified as priority by SG26. Further work is needed to resolve some of the issues and to produce covariances for the full set of 52 materials.
Food additives are substances that become part of a food product when they are added during the processing or making of that food. "Direct" food additives are often added during processing to: Add nutrients ...
Multivariate analysis of noise in genetic regulatory networks.
Tomioka, Ryota; Kimura, Hidenori; J Kobayashi, Tetsuya; Aihara, Kazuyuki
2004-08-21
Stochasticity is an intrinsic property of genetic regulatory networks due to the low copy numbers of the major molecular species, such as, DNA, mRNA, and regulatory proteins. Therefore, investigation of the mechanisms that reduce the stochastic noise is essential in understanding the reproducible behaviors of real organisms and is also a key to design synthetic genetic regulatory networks that can reliably work. We use an analytical and systematic method, the linear noise approximation of the chemical master equation along with the decoupling of a stoichiometric matrix. In the analysis of fluctuations of multiple molecular species, the covariance is an important measure of noise. However, usually the representation of a covariance matrix in the natural coordinate system, i.e. the copy numbers of the molecular species, is intractably complicated because reactions change copy numbers of more than one molecular species simultaneously. Decoupling of a stoichiometric matrix, which is a transformation of variables, significantly simplifies the representation of a covariance matrix and elucidates the mechanisms behind the observed fluctuations in the copy numbers. We apply our method to three types of fundamental genetic regulatory networks, that is, a single-gene autoregulatory network, a two-gene autoregulatory network, and a mutually repressive network. We have found that there are multiple noise components differently originating. Each noise component produces fluctuation in the characteristic direction. The resulting fluctuations in the copy numbers of the molecular species are the sum of these fluctuations. In the examples, the limitation of the negative feedback in noise reduction and the trade-off of fluctuations in multiple molecular species are clearly explained. The analytical representations show the full parameter dependence. Additionally, the validity of our method is tested by stochastic simulations. PMID:15246787
Spencer, Michael
1974-01-01
Food additives are discussed from the food technology point of view. The reasons for their use are summarized: (1) to protect food from chemical and microbiological attack; (2) to even out seasonal supplies; (3) to improve their eating quality; (4) to improve their nutritional value. The various types of food additives are considered, e.g. colours, flavours, emulsifiers, bread and flour additives, preservatives, and nutritional additives. The paper concludes with consideration of those circumstances in which the use of additives is (a) justified and (b) unjustified. PMID:4467857
Alfred Stadler, Franz Gross
2010-10-01
We provide a short overview of the Covariant Spectator Theory and its applications. The basic ideas are introduced through the example of a {phi}{sup 4}-type theory. High-precision models of the two-nucleon interaction are presented and the results of their use in calculations of properties of the two- and three-nucleon systems are discussed. A short summary of applications of this framework to other few-body systems is also presented.
Bryan, M.F.; Piepel, G.F.; Simpson, D.B.
1996-03-01
The high-level waste (HLW) vitrification plant at the Hanford Site was being designed to transuranic and high-level radioactive waste in borosilicate class. Each batch of plant feed material must meet certain requirements related to plant performance, and the resulting class must meet requirements imposed by the Waste Acceptance Product Specifications. Properties of a process batch and the resultlng glass are largely determined by the composition of the feed material. Empirical models are being developed to estimate some property values from data on feed composition. Methods for checking and documenting compliance with feed and glass requirements must account for various types of uncertainties. This document focuses on the estimation. manipulation, and consequences of composition uncertainty, i.e., the uncertainty inherent in estimates of feed or glass composition. Three components of composition uncertainty will play a role in estimating and checking feed and glass properties: batch-to-batch variability, within-batch uncertainty, and analytical uncertainty. In this document, composition uncertainty and its components are treated in terms of variances and variance components or univariate situations, covariance matrices and covariance components for multivariate situations. The importance of variance and covariance components stems from their crucial role in properly estimating uncertainty In values calculated from a set of observations on a process batch. Two general types of methods for estimating uncertainty are discussed: (1) methods based on data, and (2) methods based on knowledge, assumptions, and opinions about the vitrification process. Data-based methods for estimating variances and covariance matrices are well known. Several types of data-based methods exist for estimation of variance components; those based on the statistical method analysis of variance are discussed, as are the strengths and weaknesses of this approach.
A pure $S$-wave covariant model for the nucleon
Franz Gross; G. Ramalho; M.T. Pena
2008-01-01
Using the manifestly covariant spectator theory, and modeling the nucleon as a system of three constituent quarks with their own electromagnetic structure, we show that all four nucleon electromagnetic form factors can be very well described by a manifestly covariant nucleon wave function with zero orbital angular momentum.
Handling Correlations between Covariates and Random Slopes in Multilevel Models
ERIC Educational Resources Information Center
Bates, Michael David; Castellano, Katherine E.; Rabe-Hesketh, Sophia; Skrondal, Anders
2014-01-01
This article discusses estimation of multilevel/hierarchical linear models that include cluster-level random intercepts and random slopes. Viewing the models as structural, the random intercepts and slopes represent the effects of omitted cluster-level covariates that may be correlated with included covariates. The resulting correlations between…
Covariation Is a Poor Measure of Molecular Coevolution.
Talavera, David; Lovell, Simon C; Whelan, Simon
2015-09-01
Recent developments in the analysis of amino acid covariation are leading to breakthroughs in protein structure prediction, protein design, and prediction of the interactome. It is assumed that observed patterns of covariation are caused by molecular coevolution, where substitutions at one site affect the evolutionary forces acting at neighboring sites. Our theoretical and empirical results cast doubt on this assumption. We demonstrate that the strongest coevolutionary signal is a decrease in evolutionary rate and that unfeasibly long times are required to produce coordinated substitutions. We find that covarying substitutions are mostly found on different branches of the phylogenetic tree, indicating that they are independent events that may or may not be attributable to coevolution. These observations undermine the hypothesis that molecular coevolution is the primary cause of the covariation signal. In contrast, we find that the pairs of residues with the strongest covariation signal tend to have low evolutionary rates, and that it is this low rate that gives rise to the covariation signal. Slowly evolving residue pairs are disproportionately located in the protein's core, which explains covariation methods' ability to detect pairs of residues that are close in three dimensions. These observations lead us to propose the "coevolution paradox": The strength of coevolution required to cause coordinated changes means the evolutionary rate is so low that such changes are highly unlikely to occur. As modern covariation methods may lead to breakthroughs in structural genomics, it is critical to recognize their biases and limitations. PMID:25944916
CHANGING THE SUPPORT OF A SPATIAL COVARIATE: A SIMULATION STUDY
Technology Transfer Automated Retrieval System (TEKTRAN)
Researchers are increasingly able to capture spatially referenced data on both a response and a covariate more frequently and in more detail. A combination of geostatisical models and analysis of covariance methods is used to analyze such data. However, basic questions regarding the effects of using...
Performance of internal covariance estimators for cosmic shear correlation functions
NASA Astrophysics Data System (ADS)
Friedrich, O.; Seitz, S.; Eifler, T. F.; Gruen, D.
2016-03-01
Data re-sampling methods such as delete-one jackknife, bootstrap or the sub-sample covariance are common tools for estimating the covariance of large-scale structure probes. We investigate different implementations of these methods in the context of cosmic shear two-point statistics. Using lognormal simulations of the convergence field and the corresponding shear field we generate mock catalogues of a known and realistic covariance. For a survey of {˜ } 5000 ° ^2 we find that jackknife, if implemented by deleting sub-volumes of galaxies, provides the most reliable covariance estimates. Bootstrap, in the common implementation of drawing sub-volumes of galaxies, strongly overestimates the statistical uncertainties. In a forecast for the complete 5-yr Dark Energy Survey, we show that internally estimated covariance matrices can provide a large fraction of the true uncertainties on cosmological parameters in a 2D cosmic shear analysis. The volume inside contours of constant likelihood in the Ωm-σ8 plane as measured with internally estimated covariance matrices is on average ≳85 per cent of the volume derived from the true covariance matrix. The uncertainty on the parameter combination Σ _8 ˜ σ _8 Ω _m^{0.5} derived from internally estimated covariances is ˜90 per cent of the true uncertainty.
Covariate Balance in Bayesian Propensity Score Approaches for Observational Studies
ERIC Educational Resources Information Center
Chen, Jianshen; Kaplan, David
2015-01-01
Bayesian alternatives to frequentist propensity score approaches have recently been proposed. However, few studies have investigated their covariate balancing properties. This article compares a recently developed two-step Bayesian propensity score approach to the frequentist approach with respect to covariate balance. The effects of different…
The Regression Trunk Approach to Discover Treatment Covariate Interaction
ERIC Educational Resources Information Center
Dusseldorp, Elise; Meulman, Jacqueline J.
2004-01-01
The regression trunk approach (RTA) is an integration of regression trees and multiple linear regression analysis. In this paper RTA is used to discover treatment covariate interactions, in the regression of one continuous variable on a treatment variable with "multiple" covariates. The performance of RTA is compared to the classical method of…
Conditional Covariance Theory and Detect for Polytomous Items
ERIC Educational Resources Information Center
Zhang, Jinming
2007-01-01
This paper extends the theory of conditional covariances to polytomous items. It has been proven that under some mild conditions, commonly assumed in the analysis of response data, the conditional covariance of two items, dichotomously or polytomously scored, given an appropriately chosen composite is positive if, and only if, the two items…
Alternative Multiple Imputation Inference for Mean and Covariance Structure Modeling
ERIC Educational Resources Information Center
Lee, Taehun; Cai, Li
2012-01-01
Model-based multiple imputation has become an indispensable method in the educational and behavioral sciences. Mean and covariance structure models are often fitted to multiply imputed data sets. However, the presence of multiple random imputations complicates model fit testing, which is an important aspect of mean and covariance structure…
UDU/T/ covariance factorization for Kalman filtering
NASA Technical Reports Server (NTRS)
Thornton, C. L.; Bierman, G. J.
1980-01-01
There has been strong motivation to produce numerically stable formulations of the Kalman filter algorithms because it has long been known that the original discrete-time Kalman formulas are numerically unreliable. Numerical instability can be avoided by propagating certain factors of the estimate error covariance matrix rather than the covariance matrix itself. This paper documents filter algorithms that correspond to the covariance factorization P = UDU(T), where U is a unit upper triangular matrix and D is diagonal. Emphasis is on computational efficiency and numerical stability, since these properties are of key importance in real-time filter applications. The history of square-root and U-D covariance filters is reviewed. Simple examples are given to illustrate the numerical inadequacy of the Kalman covariance filter algorithms; these examples show how factorization techniques can give improved computational reliability.
HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS
Fan, Jianqing; Liao, Yuan; Mincheva, Martina
2012-01-01
The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied. PMID:22661790
Fraser, F C
1974-09-01
A workshop was sponsored by the National Genetics Foundation to evaluate and make recommendations about the status of genetic counseling, its goals, nature, achievements, and needs. The process of genetic workup and counseling is divided into 5 stages: validation of the diagnosis; obtaining family history; estimation of the risk of recurrence; helping the family make a decision and take appropriate action; and extending counseling to other members of the family. Counseling can be directed at individuals or at special groups with the potential of carrying such diseases as sickle cell amenia or Tay-Sachs. No consensus exists on an optimal counseling approach. Genetic counseling is regarded as a team effort, requiring, in addition to the counselor, laboratory facilities and a variety of specialists. The source of payment for genetic counseling services is regarded as a problem of increasing concern. Generally, the fee paid rarely covers the cost of the many procedures and it is suggested that the cost, like that of other public health services, should be subsidized by the state. Considerable argument exists over whether a genetic counselor must have a M.D. degree or whether a Ph. D. in medical genetics is suitable enough. The quality of much genetic counseling, which is often done in the office of doctors unskilled in the field, would be increased if better training in genetics were offered to medical students and if physicians were informed of the existence of counseling centers. Further, there is a growing feeling that some sort of accreditation of genetic counselors is desirable. PMID:4609197
NASA Astrophysics Data System (ADS)
Berge, Léonie; Litaize, Olivier; Serot, Olivier; Archier, Pascal; De Saint Jean, Cyrille; Pénéliau, Yannick; Regnier, David
2016-02-01
As the need for precise handling of nuclear data covariances grows ever stronger, no information about covariances of prompt fission neutron spectra (PFNS) are available in the evaluated library JEFF-3.2, although present in ENDF/B-VII.1 and JENDL-4.0 libraries for the main fissile isotopes. The aim of this work is to provide an estimation of covariance matrices related to PFNS, in the frame of some commonly used models for the evaluated files, such as the Maxwellian spectrum, the Watt spectrum, or the Madland-Nix spectrum. The evaluation of PFNS through these models involves an adjustment of model parameters to available experimental data, and the calculation of the spectrum variance-covariance matrix arising from experimental uncertainties. We present the results for thermal neutron induced fission of 235U. The systematic experimental uncertainties are propagated via the marginalization technique available in the CONRAD code. They are of great influence on the final covariance matrix, and therefore, on the spectrum uncertainty band width. In addition to this covariance estimation work, we have also investigated the importance on a reactor calculation of the fission spectrum model choice. A study of the vessel fluence depending on the PFNS model is presented. This is done through the propagation of neutrons emitted from a fission source in a simplified PWR using the TRIPOLI-4® code. This last study includes thermal fission spectra from the FIFRELIN Monte-Carlo code dedicated to the simulation of prompt particles emission during fission.
Petelle, M B; Martin, J G A; Blumstein, D T
2015-10-01
Describing and quantifying animal personality is now an integral part of behavioural studies because individually distinctive behaviours have ecological and evolutionary consequences. Yet, to fully understand how personality traits may respond to selection, one must understand the underlying heritability and genetic correlations between traits. Previous studies have reported a moderate degree of heritability of personality traits, but few of these studies have either been conducted in the wild or estimated the genetic correlations between personality traits. Estimating the additive genetic variance and covariance in the wild is crucial to understand the evolutionary potential of behavioural traits. Enhanced environmental variation could reduce heritability and genetic correlations, thus leading to different evolutionary predictions. We estimated the additive genetic variance and covariance of docility in the trap, sociability (mirror image stimulation), and exploration and activity in two different contexts (open-field and mirror image simulation experiments) in a wild population of yellow-bellied marmots (Marmota flaviventris). We estimated both heritability of behaviours and of personality traits and found nonzero additive genetic variance in these traits. We also found nonzero maternal, permanent environment and year effects. Finally, we found four phenotypic correlations between traits, and one positive genetic correlation between activity in the open-field test and sociability. We also found permanent environment correlations between activity in both tests and docility and exploration in the MIS test. This is one of a handful of studies to adopt a quantitative genetic approach to explain variation in personality traits in the wild and, thus, provides important insights into the potential variance available for selection. PMID:26214760
Functional Generalized Additive Models.
McLean, Mathew W; Hooker, Giles; Staicu, Ana-Maria; Scheipl, Fabian; Ruppert, David
2014-01-01
We introduce the functional generalized additive model (FGAM), a novel regression model for association studies between a scalar response and a functional predictor. We model the link-transformed mean response as the integral with respect to t of F{X(t), t} where F(·,·) is an unknown regression function and X(t) is a functional covariate. Rather than having an additive model in a finite number of principal components as in Müller and Yao (2008), our model incorporates the functional predictor directly and thus our model can be viewed as the natural functional extension of generalized additive models. We estimate F(·,·) using tensor-product B-splines with roughness penalties. A pointwise quantile transformation of the functional predictor is also considered to ensure each tensor-product B-spline has observed data on its support. The methods are evaluated using simulated data and their predictive performance is compared with other competing scalar-on-function regression alternatives. We illustrate the usefulness of our approach through an application to brain tractography, where X(t) is a signal from diffusion tensor imaging at position, t, along a tract in the brain. In one example, the response is disease-status (case or control) and in a second example, it is the score on a cognitive test. R code for performing the simulations and fitting the FGAM can be found in supplemental materials available online. PMID:24729671
A Population Genetic Signal of Polygenic Adaptation
Berg, Jeremy J.; Coop, Graham
2014-01-01
Adaptation in response to selection on polygenic phenotypes may occur via subtle allele frequencies shifts at many loci. Current population genomic techniques are not well posed to identify such signals. In the past decade, detailed knowledge about the specific loci underlying polygenic traits has begun to emerge from genome-wide association studies (GWAS). Here we combine this knowledge from GWAS with robust population genetic modeling to identify traits that may have been influenced by local adaptation. We exploit the fact that GWAS provide an estimate of the additive effect size of many loci to estimate the mean additive genetic value for a given phenotype across many populations as simple weighted sums of allele frequencies. We use a general model of neutral genetic value drift for an arbitrary number of populations with an arbitrary relatedness structure. Based on this model, we develop methods for detecting unusually strong correlations between genetic values and specific environmental variables, as well as a generalization of comparisons to test for over-dispersion of genetic values among populations. Finally we lay out a framework to identify the individual populations or groups of populations that contribute to the signal of overdispersion. These tests have considerably greater power than their single locus equivalents due to the fact that they look for positive covariance between like effect alleles, and also significantly outperform methods that do not account for population structure. We apply our tests to the Human Genome Diversity Panel (HGDP) dataset using GWAS data for height, skin pigmentation, type 2 diabetes, body mass index, and two inflammatory bowel disease datasets. This analysis uncovers a number of putative signals of local adaptation, and we discuss the biological interpretation and caveats of these results. PMID:25102153
Correcting eddy-covariance flux underestimates over a grassland.
Twine, T. E.; Kustas, W. P.; Norman, J. M.; Cook, D. R.; Houser, P. R.; Meyers, T. P.; Prueger, J. H.; Starks, P. J.; Wesely, M. L.; Environmental Research; Univ. of Wisconsin at Madison; DOE; National Aeronautics and Space Administration; National Oceanic and Atmospheric Administrationoratory
2000-06-08
Independent measurements of the major energy balance flux components are not often consistent with the principle of conservation of energy. This is referred to as a lack of closure of the surface energy balance. Most results in the literature have shown the sum of sensible and latent heat fluxes measured by eddy covariance to be less than the difference between net radiation and soil heat fluxes. This under-measurement of sensible and latent heat fluxes by eddy-covariance instruments has occurred in numerous field experiments and among many different manufacturers of instruments. Four eddy-covariance systems consisting of the same models of instruments were set up side-by-side during the Southern Great Plains 1997 Hydrology Experiment and all systems under-measured fluxes by similar amounts. One of these eddy-covariance systems was collocated with three other types of eddy-covariance systems at different sites; all of these systems under-measured the sensible and latent-heat fluxes. The net radiometers and soil heat flux plates used in conjunction with the eddy-covariance systems were calibrated independently and measurements of net radiation and soil heat flux showed little scatter for various sites. The 10% absolute uncertainty in available energy measurements was considerably smaller than the systematic closure problem in the surface energy budget, which varied from 10 to 30%. When available-energy measurement errors are known and modest, eddy-covariance measurements of sensible and latent heat fluxes should be adjusted for closure. Although the preferred method of energy balance closure is to maintain the Bowen-ratio, the method for obtaining closure appears to be less important than assuring that eddy-covariance measurements are consistent with conservation of energy. Based on numerous measurements over a sorghum canopy, carbon dioxide fluxes, which are measured by eddy covariance, are underestimated by the same factor as eddy covariance evaporation
Predicting the risk of toxic blooms of golden alga from cell abundance and environmental covariates
Patino, Reynaldo; VanLandeghem, Matthew M.; Denny, Shawn
2016-01-01
Golden alga (Prymnesium parvum) is a toxic haptophyte that has caused considerable ecological damage to marine and inland aquatic ecosystems worldwide. Studies focused primarily on laboratory cultures have indicated that toxicity is poorly correlated with the abundance of golden alga cells. This relationship, however, has not been rigorously evaluated in the field where environmental conditions are much different. The ability to predict toxicity using readily measured environmental variables and golden alga abundance would allow managers rapid assessments of ichthyotoxicity potential without laboratory bioassay confirmation, which requires additional resources to accomplish. To assess the potential utility of these relationships, several a priori models relating lethal levels of golden alga ichthyotoxicity to golden alga abundance and environmental covariates were constructed. Model parameters were estimated using archived data from four river basins in Texas and New Mexico (Colorado, Brazos, Red, Pecos). Model predictive ability was quantified using cross-validation, sensitivity, and specificity, and the relative ranking of environmental covariate models was determined by Akaike Information Criterion values and Akaike weights. Overall, abundance was a generally good predictor of ichthyotoxicity as cross validation of golden alga abundance-only models ranged from ∼ 80% to ∼ 90% (leave-one-out cross-validation). Environmental covariates improved predictions, especially the ability to predict lethally toxic events (i.e., increased sensitivity), and top-ranked environmental covariate models differed among the four basins. These associations may be useful for monitoring as well as understanding the abiotic factors that influence toxicity during blooms.
Super-sample covariance in simulations
NASA Astrophysics Data System (ADS)
Li, Yin; Hu, Wayne; Takada, Masahiro
2014-04-01
Using separate universe simulations, we accurately quantify super-sample covariance (SSC), the typically dominant sampling error for matter power spectrum estimators in a finite volume, which arises from the presence of super survey modes. By quantifying the power spectrum response to a background mode, this approach automatically captures the separate effects of beat coupling in the quasilinear regime, halo sample variance in the nonlinear regime and a new dilation effect which changes scales in the power spectrum coherently across the survey volume, including the baryon acoustic oscillation scale. It models these effects at typically the few percent level or better with a handful of small volume simulations for any survey geometry compared with directly using many thousands of survey volumes in a suite of large-volume simulations. The stochasticity of the response is sufficiently small that in the quasilinear regime, SSC can be alternately included by fitting the mean density in the volume with these fixed templates in parameter estimation. We also test the halo model prescription and find agreement typically at better than the 10% level for the response.
The Hopfield model revisited: covariance and quantization
NASA Astrophysics Data System (ADS)
Belgiorno, F.; Cacciatori, S. L.; Dalla Piazza, F.
2016-01-01
There are several possible applications of quantum electrodynamics in dielectric media which require a quantum description for the electromagnetic field interacting with matter fields. The associated quantum models can refer to macroscopic electromagnetic fields or, alternatively, to mesoscopic fields (polarization fields) describing an effective interaction between electromagnetic field and matter fields. We adopt the latter approach, and focus on the Hopfield model for the electromagnetic field in a dielectric dispersive medium in a framework in which space-time dependent mesoscopic parameters occur, like susceptibility, matter resonance frequency, and also coupling between electromagnetic field and polarization field. Our most direct goal is to describe in a phenomenological way a space-time varying dielectric perturbation induced by means of the Kerr effect in nonlinear dielectric media. This extension of the model is implemented by means of a Lorentz-invariant Lagrangian which, for constant microscopic parameters, and in the rest frame, coincides with the standard one. Moreover, we deduce a covariant scalar product and provide a canonical quantization scheme which takes into account the constraints implicit in the model. Examples of viable applications are indicated.
Holographic bound in covariant loop quantum gravity
NASA Astrophysics Data System (ADS)
Tamaki, Takashi
2016-07-01
We investigate puncture statistics based on the covariant area spectrum in loop quantum gravity. First, we consider Maxwell-Boltzmann statistics with a Gibbs factor for punctures. We establish formulas which relate physical quantities such as horizon area to the parameter characterizing holographic degrees of freedom. We also perform numerical calculations and obtain consistency with these formulas. These results tell us that the holographic bound is satisfied in the large area limit and the correction term of the entropy-area law can be proportional to the logarithm of the horizon area. Second, we also consider Bose-Einstein statistics and show that the above formulas are also useful in this case. By applying the formulas, we can understand intrinsic features of Bose-Einstein condensate which corresponds to the case when the horizon area almost consists of punctures in the ground state. When this phenomena occurs, the area is approximately constant against the parameter characterizing the temperature. When this phenomena is broken, the area shows rapid increase which suggests the phase transition from quantum to classical area.
Canonical quantization of Galilean covariant field theories
NASA Astrophysics Data System (ADS)
Santos, E. S.; de Montigny, M.; Khanna, F. C.
2005-11-01
The Galilean-invariant field theories are quantized by using the canonical method and the five-dimensional Lorentz-like covariant expressions of non-relativistic field equations. This method is motivated by the fact that the extended Galilei group in 3 + 1 dimensions is a subgroup of the inhomogeneous Lorentz group in 4 + 1 dimensions. First, we consider complex scalar fields, where the Schrödinger field follows from a reduction of the Klein-Gordon equation in the extended space. The underlying discrete symmetries are discussed, and we calculate the scattering cross-sections for the Coulomb interaction and for the self-interacting term λΦ4. Then, we turn to the Dirac equation, which, upon dimensional reduction, leads to the Lévy-Leblond equations. Like its relativistic analogue, the model allows for the existence of antiparticles. Scattering amplitudes and cross-sections are calculated for the Coulomb interaction, the electron-electron and the electron-positron scattering. These examples show that the so-called 'non-relativistic' approximations, obtained in low-velocity limits, must be treated with great care to be Galilei-invariant. The non-relativistic Proca field is discussed briefly.
Generalized Covariant Gyrokinetic Dynamics of Magnetoplasmas
Cremaschini, C.; Tessarotto, M.; Nicolini, P.; Beklemishev, A.
2008-12-31
A basic prerequisite for the investigation of relativistic astrophysical magnetoplasmas, occurring typically in the vicinity of massive stellar objects (black holes, neutron stars, active galactic nuclei, etc.), is the accurate description of single-particle covariant dynamics, based on gyrokinetic theory (Beklemishev et al., 1999-2005). Provided radiation-reaction effects are negligible, this is usually based on the assumption that both the space-time metric and the EM fields (in particular the magnetic field) are suitably prescribed and are considered independent of single-particle dynamics, while allowing for the possible presence of gravitational/EM perturbations driven by plasma collective interactions which may naturally arise in such systems. The purpose of this work is the formulation of a generalized gyrokinetic theory based on the synchronous variational principle recently pointed out (Tessarotto et al., 2007) which permits to satisfy exactly the physical realizability condition for the four-velocity. The theory here developed includes the treatment of nonlinear perturbations (gravitational and/or EM) characterized locally, i.e., in the rest frame of a test particle, by short wavelength and high frequency. Basic feature of the approach is to ensure the validity of the theory both for large and vanishing parallel electric field. It is shown that the correct treatment of EM perturbations occurring in the presence of an intense background magnetic field generally implies the appearance of appropriate four-velocity corrections, which are essential for the description of single-particle gyrokinetic dynamics.
Clustered data analysis under miscategorized ordinal outcomes and missing covariates.
Roy, Surupa; Rana, Subrata; Das, Kalyan
2016-08-15
The primary objective in this article is to look into the analysis of clustered ordinal model where complete information on one or more covariates cease to occur. In addition, we also focus on the analysis of miscategorized data that occur in many situations as outcomes are often classified into a category that does not truly reflect its actual state. A general model structure is assumed to accommodate the information that is obtained via surrogate variables. The theoretical motivation actually developed while encountering an orthodontic data to investigate the effects of age, sex and food habit on the extent of plaque deposit. The model we propose is quite flexible and is capable of tackling those additional noises like miscategorization and missingness, which occur in the data most frequently. A new two-step approach has been proposed to estimate the parameters of model framed. A rigorous simulation study has also been carried out to justify the validity of the model taken up for analysis. Copyright © 2015 John Wiley & Sons, Ltd. PMID:26215983
Fox, Andrew; Williams, Mathew; Richardson, Andrew D.; Cameron, David; Gove, Jeffrey H.; Quaife, Tristan; Ricciuto, Daniel M; Reichstein, Markus; Tomelleri, Enrico; Trudinger, Cathy; Van Wijk, Mark T.
2009-10-01
We describe a model-data fusion (MDF) inter-comparison project (REFLEX), which compared various algorithms for estimating carbon (C) model parameters consistent with both measured carbon fluxes and states and a simple C model. Participants were provided with the model and with both synthetic net ecosystem exchange (NEE) ofCO2 and leaf area index (LAI) data, generated from the model with added noise, and observed NEE and LAI data from two eddy covariance sites. Participants endeavoured to estimate model parameters and states consistent with the model for all cases over the two years for which data were provided, and generate predictions for one additional year without observations. Nine participants contributed results using Metropolis algorithms, Kalman filters and a genetic algorithm. For the synthetic data case, parameter estimates compared well with the true values. The results of the analyses indicated that parameters linked directly to gross primary production (GPP) and ecosystem respiration, such as those related to foliage allocation and turnover, or temperature sensitivity of heterotrophic respiration,were best constrained and characterised. Poorly estimated parameters were those related to the allocation to and turnover of fine root/wood pools. Estimates of confidence intervals varied among algorithms, but several algorithms successfully located the true values of annual fluxes from synthetic experiments within relatively narrow 90% confidence intervals, achieving>80% success rate and mean NEE confidence intervals <110 gCm-2 year-1 for the synthetic case. Annual C flux estimates generated by participants generally agreed with gap-filling approaches using half-hourly data. The estimation of ecosystem respiration and GPP through MDF agreed well with outputs from partitioning studies using half-hourly data. Confidence limits on annual NEE increased by an average of 88% in the prediction year compared to the previous year, when data were available. Confidence
Lopes, Fernando Brito; Magnabosco, Cláudio Ulhôa; Paulini, Fernanda; da Silva, Marcelo Corrêa; Miyagi, Eliane Sayuri; Lôbo, Raysildo Barbosa
2013-01-01
Components of (co)variance and genetic parameters were estimated for adjusted weights at ages 120 (W120), 240 (W240), 365 (W365) and 450 (W450) days of Polled Nellore cattle raised on pasture and born between 1987 and 2010. Analyses were performed using an animal model, considering fixed effects: herd-year-season of birth and calf sex as contemporary groups and the age of cow as a covariate. Gibbs Samplers were used to estimate (co)variance components, genetic parameters and additive genetic effects, which accounted for great proportion of total variation in these traits. High direct heritability estimates for the growth traits were revealed and presented mean 0.43, 0.61, 0.72 and 0.67 for W120, W240, W365 and W450, respectively. Maternal heritabilities were 0.07 and 0.08 for W120 and W240, respectively. Direct additive genetic correlations between the weight at 120, 240, 365 and 450 days old were strong and positive. These estimates ranged from 0.68 to 0.98. Direct-maternal genetic correlations were negative for W120 and W240. The estimates ranged from −0.31 to −0.54. Estimates of maternal heritability ranged from 0.056 to 0.092 for W120 and from 0.064 to 0.096 for W240. This study showed that genetic progress is possible for the growth traits we studied, which is a novel and favorable indicator for an upcoming and promising Polled Zebu breed in Tropical regions. Maternal effects influenced the performance of weight at 120 and 240 days old. These effects should be taken into account in genetic analyses of growth traits by fitting them as a genetic or a permanent environmental effect, or even both. In general, due to a medium-high estimate of environmental (co)variance components, management and feeding conditions for Polled Nellore raised at pasture in tropical regions of Brazil needs improvement and growth performance can be enhanced. PMID:24040412
Genetic and cultural transmission of antisocial behavior: an extended twin parent model.
Maes, Hermine H; Silberg, Judy L; Neale, Michael C; Eaves, Lindon J
2007-02-01
Considerable evidence from twin and adoption studies indicates that both genetic and shared environmental factors play a substantial role in the liability to antisocial behavior. Although twin and adoption designs can resolve genetic and environmental influences, they do not provide information about assortative mating, parent-offspring transmission, or the contribution of these factors to trait variation. We examined the role of genetic and environmental factors for conduct disorder (CD) using a twin-parent design. This design allows the simultaneous estimation of additive genetic, shared and individual-specific environmental effects, as well as sex differences in the expression of genes and environment in the presence of assortative mating and combined genetic and cultural transmission. A retrospective measure of CD was obtained from twins and their parents or guardians in the Virginia Twin Study of Adolescent Behavior Development and its Young Adult Follow up sample. Both genetic and environmental factors play a significant role in the liability to CD. Major influences on individual differences appeared to be additive genetic (38%-40%) and unique environmental (39%-42%) effects, with smaller contributions from the shared environment (18%-23%), assortative mating (-2%), cultural transmission (approximately 2%) and resulting genotype-environment covariance. This study showed significant heritability, which is slightly increased by assortative mating, and significant effects of primarily nonparental shared environment on CD. PMID:17539373
Quantification of Covariance in Tropical Cyclone Activity across Teleconnected Basins
NASA Astrophysics Data System (ADS)
Tolwinski-Ward, S. E.; Wang, D.
2015-12-01
Rigorous statistical quantification of natural hazard covariance across regions has important implications for risk management, and is also of fundamental scientific interest. We present a multivariate Bayesian Poisson regression model for inferring the covariance in tropical cyclone (TC) counts across multiple ocean basins and across Saffir-Simpson intensity categories. Such covariability results from the influence of large-scale modes of climate variability on local environments that can alternately suppress or enhance TC genesis and intensification, and our model also simultaneously quantifies the covariance of TC counts with various climatic modes in order to deduce the source of inter-basin TC covariability. The model explicitly treats the time-dependent uncertainty in observed maximum sustained wind data, and hence the nominal intensity category of each TC. Differences in annual TC counts as measured by different agencies are also formally addressed. The probabilistic output of the model can be probed for probabilistic answers to such questions as: - Does the relationship between different categories of TCs differ statistically by basin? - Which climatic predictors have significant relationships with TC activity in each basin? - Are the relationships between counts in different basins conditionally independent given the climatic predictors, or are there other factors at play affecting inter-basin covariability? - How can a portfolio of insured property be optimized across space to minimize risk? Although we present results of our model applied to TCs, the framework is generalizable to covariance estimation between multivariate counts of natural hazards across regions and/or across peril types.
Action recognition from video using feature covariance matrices.
Guo, Kai; Ishwar, Prakash; Konrad, Janusz
2013-06-01
We propose a general framework for fast and accurate recognition of actions in video using empirical covariance matrices of features. A dense set of spatio-temporal feature vectors are computed from video to provide a localized description of the action, and subsequently aggregated in an empirical covariance matrix to compactly represent the action. Two supervised learning methods for action recognition are developed using feature covariance matrices. Common to both methods is the transformation of the classification problem in the closed convex cone of covariance matrices into an equivalent problem in the vector space of symmetric matrices via the matrix logarithm. The first method applies nearest-neighbor classification using a suitable Riemannian metric for covariance matrices. The second method approximates the logarithm of a query covariance matrix by a sparse linear combination of the logarithms of training covariance matrices. The action label is then determined from the sparse coefficients. Both methods achieve state-of-the-art classification performance on several datasets, and are robust to action variability, viewpoint changes, and low object resolution. The proposed framework is conceptually simple and has low storage and computational requirements making it attractive for real-time implementation. PMID:23508265
Berglund, F
1978-01-01
The use of additives to food fulfils many purposes, as shown by the index issued by the Codex Committee on Food Additives: Acids, bases and salts; Preservatives, Antioxidants and antioxidant synergists; Anticaking agents; Colours; Emulfifiers; Thickening agents; Flour-treatment agents; Extraction solvents; Carrier solvents; Flavours (synthetic); Flavour enhancers; Non-nutritive sweeteners; Processing aids; Enzyme preparations. Many additives occur naturally in foods, but this does not exclude toxicity at higher levels. Some food additives are nutrients, or even essential nutritents, e.g. NaCl. Examples are known of food additives causing toxicity in man even when used according to regulations, e.g. cobalt in beer. In other instances, poisoning has been due to carry-over, e.g. by nitrate in cheese whey - when used for artificial feed for infants. Poisonings also occur as the result of the permitted substance being added at too high levels, by accident or carelessness, e.g. nitrite in fish. Finally, there are examples of hypersensitivity to food additives, e.g. to tartrazine and other food colours. The toxicological evaluation, based on animal feeding studies, may be complicated by impurities, e.g. orthotoluene-sulfonamide in saccharin; by transformation or disappearance of the additive in food processing in storage, e.g. bisulfite in raisins; by reaction products with food constituents, e.g. formation of ethylurethane from diethyl pyrocarbonate; by metabolic transformation products, e.g. formation in the gut of cyclohexylamine from cyclamate. Metabolic end products may differ in experimental animals and in man: guanylic acid and inosinic acid are metabolized to allantoin in the rat but to uric acid in man. The magnitude of the safety margin in man of the Acceptable Daily Intake (ADI) is not identical to the "safety factor" used when calculating the ADI. The symptoms of Chinese Restaurant Syndrome, although not hazardous, furthermore illustrate that the whole ADI
Genome-Wide Scan for Adaptive Divergence and Association with Population-Specific Covariates.
Gautier, Mathieu
2015-12-01
In population genomics studies, accounting for the neutral covariance structure across population allele frequencies is critical to improve the robustness of genome-wide scan approaches. Elaborating on the BayEnv model, this study investigates several modeling extensions (i) to improve the estimation accuracy of the population covariance matrix and all the related measures, (ii) to identify significantly overly differentiated SNPs based on a calibration procedure of the XtX statistics, and (iii) to consider alternative covariate models for analyses of association with population-specific covariables. In particular, the auxiliary variable model allows one to deal with multiple testing issues and, providing the relative marker positions are available, to capture some linkage disequilibrium information. A comprehensive simulation study was carried out to evaluate the performances of these different models. Also, when compared in terms of power, robustness, and computational efficiency to five other state-of-the-art genome-scan methods (BayEnv2, BayScEnv, BayScan, flk, and lfmm), the proposed approaches proved highly effective. For illustration purposes, genotyping data on 18 French cattle breeds were analyzed, leading to the identification of 13 strong signatures of selection. Among these, four (surrounding the KITLG, KIT, EDN3, and ALB genes) contained SNPs strongly associated with the piebald coloration pattern while a fifth (surrounding PLAG1) could be associated to morphological differences across the populations. Finally, analysis of Pool-Seq data from 12 populations of Littorina saxatilis living in two different ecotypes illustrates how the proposed framework might help in addressing relevant ecological issues in nonmodel species. Overall, the proposed methods define a robust Bayesian framework to characterize adaptive genetic differentiation across populations. The BayPass program implementing the different models is available at http://www1.montpellier
Recurrence Analysis of Eddy Covariance Fluxes
NASA Astrophysics Data System (ADS)
Lange, Holger; Flach, Milan; Foken, Thomas; Hauhs, Michael
2015-04-01
The eddy covariance (EC) method is one key method to quantify fluxes in biogeochemical cycles in general, and carbon and energy transport across the vegetation-atmosphere boundary layer in particular. EC data from the worldwide net of flux towers (Fluxnet) have also been used to validate biogeochemical models. The high resolution data are usually obtained at 20 Hz sampling rate but are affected by missing values and other restrictions. In this contribution, we investigate the nonlinear dynamics of EC fluxes using Recurrence Analysis (RA). High resolution data from the site DE-Bay (Waldstein-Weidenbrunnen) and fluxes calculated at half-hourly resolution from eight locations (part of the La Thuile dataset) provide a set of very long time series to analyze. After careful quality assessment and Fluxnet standard gapfilling pretreatment, we calculate properties and indicators of the recurrent structure based both on Recurrence Plots as well as Recurrence Networks. Time series of RA measures obtained from windows moving along the time axis are presented. Their interpretation is guided by three different questions: (1) Is RA able to discern periods where the (atmospheric) conditions are particularly suitable to obtain reliable EC fluxes? (2) Is RA capable to detect dynamical transitions (different behavior) beyond those obvious from visual inspection? (3) Does RA contribute to an understanding of the nonlinear synchronization between EC fluxes and atmospheric parameters, which is crucial for both improving carbon flux models as well for reliable interpolation of gaps? (4) Is RA able to recommend an optimal time resolution for measuring EC data and for analyzing EC fluxes? (5) Is it possible to detect non-trivial periodicities with a global RA? We will demonstrate that the answers to all five questions is affirmative, and that RA provides insights into EC dynamics not easily obtained otherwise.
Covariant hyperbolization of force-free electrodynamics
NASA Astrophysics Data System (ADS)
Carrasco, F. L.; Reula, O. A.
2016-04-01
Force-free electrodynamics (FFE) is a nonlinear system of equations modeling the evolution of the electromagnetic field, in the presence of a magnetically dominated relativistic plasma. This configuration arises on several astrophysical scenarios which represent exciting laboratories to understand physics in extreme regimes. We show that this system, when restricted to the correct constraint submanifold, is symmetric hyperbolic. In numerical applications, it is not feasible to keep the system in that submanifold, and so it is necessary to analyze its structure first in the tangent space of that submanifold and then in a whole neighborhood of it. As has been shown [1], a direct (or naive) formulation of this system (in the whole tangent space) results in a weakly hyperbolic system of evolution equations for which well-posedness for the initial value formulation does not follow. Using the generalized symmetric hyperbolic formalism of Geroch [2], we introduce here a covariant hyperbolization for the FFE system. In fact, in analogy to the usual Maxwell case, a complete family of hyperbolizers is found, both for the restricted system on the constraint submanifold as well as for a suitably extended system defined in a whole neighborhood of it. A particular symmetrizer among the family is then used to write down the pertaining evolution equations, in a generic (3 +1 ) decomposition on a background spacetime. Interestingly, it turns out that for a particular choice of the lapse and shift functions of the foliation, our symmetrized system reduces to the one found in [1]. Finally, we analyze the characteristic structure of the resulting evolution system.
Inflation in general covariant theory of gravity
Huang, Yongqing; Wang, Anzhong; Wu, Qiang E-mail: anzhong_wang@baylor.edu
2012-10-01
In this paper, we study inflation in the framework of the nonrelativistic general covariant theory of the Hořava-Lifshitz gravity with the projectability condition and an arbitrary coupling constant λ. We find that the Friedmann-Robterson-Walker (FRW) universe is necessarily flat in such a setup. We work out explicitly the linear perturbations of the flat FRW universe without specifying to a particular gauge, and find that the perturbations are different from those obtained in general relativity, because of the presence of the high-order spatial derivative terms. Applying the general formulas to a single scalar field, we show that in the sub-horizon regions, the metric and scalar field are tightly coupled and have the same oscillating frequencies. In the super-horizon regions, the perturbations become adiabatic, and the comoving curvature perturbation is constant. We also calculate the power spectra and indices of both the scalar and tensor perturbations, and express them explicitly in terms of the slow roll parameters and the coupling constants of the high-order spatial derivative terms. In particular, we find that the perturbations, of both scalar and tensor, are almost scale-invariant, and, with some reasonable assumptions on the coupling coefficients, the spectrum index of the tensor perturbation is the same as that given in the minimum scenario in general relativity (GR), whereas the index for scalar perturbation in general depends on λ and is different from the standard GR value. The ratio of the scalar and tensor power spectra depends on the high-order spatial derivative terms, and can be different from that of GR significantly.
Franz, Carol E; York, Timothy P; Eaves, Lindon J; Prom-Wormley, Elizabeth; Jacobson, Kristen C; Lyons, Michael J; Grant, Michael D; Xian, Hong; Panizzon, Matthew S; Jimenez, Erica; Kremen, William S
2011-07-01
Adult romantic attachment styles reflect ways of relating in close relationships and are associated with depression and negative emotionality. We estimated the extent to which dimensions of romantic attachment and negative emotionality share genetic or environmental risk factors in 1,237 middle-aged men in the Vietnam Era Twin Study of Aging (VETSA). A common genetic factor largely explained the covariance between attachment-related anxiety, attachment-related avoidance, depressive symptoms, and two measures of negative emotionality: Stress-Reaction (anxiety), and Alienation. Multivariate results supported genetic and environmental differences in attachment. Attachment-related anxiety and attachment-related avoidance were each influenced by additional genetic factors not shared with other measures; the genetic correlation between the attachment measure-specific genetic factors was 0.41, indicating some, but not complete overlap of genetic factors. Genetically informative longitudinal studies on attachment relationship dimensions can help to illuminate the role of relationship-based risk factors in healthy aging. PMID:21213033
Kimmel, Charles B.; Cresko, William A.; Phillips, Patrick C.; Ullmann, Bonnie; Currey, Mark; von Hippel, Frank; Kristjánsson, Bjarni K.; Gelmond, Ofer; McGuigan, Katrina
2014-01-01
Evolution of similar phenotypes in independent populations is often taken as evidence of adaptation to the same fitness optimum. However, the genetic architecture of traits might cause evolution to proceed more often toward particular phenotypes, and less often toward others, independently of the adaptive value of the traits. Freshwater populations of Alaskan threespine stickleback have repeatedly evolved the same distinctive opercle shape after divergence from an oceanic ancestor. Here we demonstrate that this pattern of parallel evolution is widespread, distinguishing oceanic and freshwater populations across the Pacific Coast of North America and Iceland. We test whether this parallel evolution reflects genetic bias by estimating the additive genetic variance– covariance matrix (G) of opercle shape in an Alaskan oceanic (putative ancestral) population. We find significant additive genetic variance for opercle shape and that G has the potential to be biasing, because of the existence of regions of phenotypic space with low additive genetic variation. However, evolution did not occur along major eigenvectors of G, rather it occurred repeatedly in the same directions of high evolvability. We conclude that the parallel opercle evolution is most likely due to selection during adaptation to freshwater habitats, rather than due to biasing effects of opercle genetic architecture. PMID:22276538
Genetic parameters for carcass traits and body size in sheep for meat production.
Figueiredo Filho, Luiz Antonio Silva; Do Ó, Alan Oliveira; Sarmento, José Lindenberg Rocha; Santos, Natanael Pereira Da Silva; Torres, Tatiana Saraiva
2016-01-01
The aim was to estimate the covariance components and genetic parameters of carcass traits and body size of meat sheep by employing animal models for single and multi-trait analyses. Data were collected from herds of adult Santa Ines sheep. The ribeye area, subcutaneous fat thickness, and rump fat thickness, evaluated in vivo by ultrasound images of the carcass; and morphometric traits: fat depth, rump height, chest circumference, chest depth, body length, and rump length were measured. The covariance components and genetic parameters for these traits were estimated by restricted maximum likelihood methodology, considering the random additive direct-genetic effects of the animal and errors associated with each observation, and the fixed effects of the contemporary group, the type of birth, and the age of the animal classes. Heritability estimates for carcass traits and animal size were higher in the three-trait analyses than in the single-trait analyses. The magnitudes of the values obtained indicate that genetic progress can be achieved by selection based on the traits studied. PMID:26462933
Covariate Adjusted Correlation Analysis with Application to FMR1 Premutation Female Carrier Data
Şentürk, Damla; Nguyen, Danh V.; Tassone, Flora; Hagerman, Randi J.; Carroll, Raymond J.; Hagerman, Paul J.
2009-01-01
Summary Motivated by molecular data on female premutation carriers of the fragile X mental retardation 1 (FMR1) gene, we present a new method of covariate adjusted correlation analysis to examine the association of messenger RNA (mRNA) and number of CGG repeat expansion in the FMR1 gene. The association between the molecular variables in female carriers needs to adjust for activation ratio (ActRatio), a measure which accounts for the protective effects of one normal X chromosome in females carriers. However, there are inherent uncertainties in the exact effects of ActRatio on the molecular measures of interest. To account for these uncertainties, we develop a flexible adjustment that accommodates both additive and multiplicative effects of ActRatio nonparametrically. The proposed adjusted correlation uses local conditional correlations, which are local method of moments estimators, to estimate the Pearson correlation between two variables adjusted for a third observable covariate. The local method of moments estimators are averaged to arrive at the final covariate adjusted correlation estimator, which is shown to be consistent. We also develop a test to check the nonparametric joint additive and multiplicative adjustment form. Simulation studies illustrate the efficacy of the proposed method. (Application to FMR1 premutation data on 165 female carriers indicates that the association between mRNA and CGG repeat after adjusting for ActRatio is stronger.) Finally, the results provide independent support for a specific jointly additive and multiplicative adjustment form for ActRatio previously proposed in the literature. PMID:19173699
The importance of covariance in nuclear data uncertainty propagation studies
Benstead, J.
2012-07-01
A study has been undertaken to investigate what proportion of the uncertainty propagated through plutonium critical assembly calculations is due to the covariances between the fission cross section in different neutron energy groups. The uncertainties on k{sub eff} calculated show that the presence of covariances between the cross section in different neutron energy groups accounts for approximately 27-37% of the propagated uncertainty due to the plutonium fission cross section. This study also confirmed the validity of employing the sandwich equation, with associated sensitivity and covariance data, instead of a Monte Carlo sampling approach to calculating uncertainties for linearly varying systems. (authors)
Hawking radiation, covariant boundary conditions, and vacuum states
Banerjee, Rabin; Kulkarni, Shailesh
2009-04-15
The basic characteristics of the covariant chiral current
Estimation of the covariance matrix of macroscopic quantum states
NASA Astrophysics Data System (ADS)
Ruppert, László; Usenko, Vladyslav C.; Filip, Radim
2016-05-01
For systems analogous to a linear harmonic oscillator, the simplest way to characterize the state is by a covariance matrix containing the symmetrically ordered moments of operators analogous to position and momentum. We show that using Stokes-like detectors without direct access to either position or momentum, the estimation of the covariance matrix of a macroscopic signal is still possible using interference with a classical noisy and low-intensity reference. Such a detection technique will allow one to estimate macroscopic quantum states of electromagnetic radiation without a coherent high-intensity local oscillator. It can be directly applied to estimate the covariance matrix of macroscopically bright squeezed states of light.
Genetic Variance in Processing Speed Drives Variation in Aging of Spatial and Memory Abilities
Finkel, Deborah; McArdle, John J.; Reynolds, Chandra A.; Hamagami, Fumiaki; Pedersen, Nancy L.
2013-01-01
Previous analyses have identified a genetic contribution to the correlation between declines with age in processing speed and higher cognitive abilities. The goal of the current analysis was to apply the biometric dual change score model to consider the possibility of temporal dynamics underlying the genetic covariance between aging trajectories for processing speed and cognitive abilities. Longitudinal twin data from the Swedish Adoption/Twin Study of Aging, including up to 5 measurement occasions covering a 16-year period, were available from 806 participants ranging in age from 50 to 88 years at the 1st measurement wave. Factors were generated to tap 4 cognitive domains: verbal ability, spatial ability, memory, and processing speed. Model-fitting indicated that genetic variance for processing speed was a leading indicator of variation in age changes for spatial and memory ability, providing additional support for processing speed theories of cognitive aging. PMID:19413434
Burke, Wylie; Tarini, Beth; Press, Nancy A.; Evans, James P.
2011-01-01
Current approaches to genetic screening include newborn screening to identify infants who would benefit from early treatment, reproductive genetic screening to assist reproductive decision making, and family history assessment to identify individuals who would benefit from additional prevention measures. Although the traditional goal of screening is to identify early disease or risk in order to implement preventive therapy, genetic screening has always included an atypical element—information relevant to reproductive decisions. New technologies offer increasingly comprehensive identification of genetic conditions and susceptibilities. Tests based on these technologies are generating a different approach to screening that seeks to inform individuals about all of their genetic traits and susceptibilities for purposes that incorporate rapid diagnosis, family planning, and expediting of research, as well as the traditional screening goal of improving prevention. Use of these tests in population screening will increase the challenges already encountered in genetic screening programs, including false-positive and ambiguous test results, overdiagnosis, and incidental findings. Whether this approach is desirable requires further empiric research, but it also requires careful deliberation on the part of all concerned, including genomic researchers, clinicians, public health officials, health care payers, and especially those who will be the recipients of this novel screening approach. PMID:21709145
Mutually unbiased bases as minimal Clifford covariant 2-designs
NASA Astrophysics Data System (ADS)
Zhu, Huangjun
2015-06-01
Mutually unbiased bases (MUBs) are interesting for various reasons. The most attractive example of (a complete set of) MUBs is the one constructed by Ivanović as well as Wootters and Fields, which is referred to as the canonical MUB. Nevertheless, little is known about anything that is unique to this MUB. We show that the canonical MUB in any prime power dimension is uniquely determined by an extremal orbit of the (restricted) Clifford group except in dimension 3, in which case the orbit defines a special symmetric informationally complete measurement (SIC), known as the Hesse SIC. Here the extremal orbit is the orbit with the smallest number of pure states. Quite surprisingly, this characterization does not rely on any concept that is related to bases or unbiasedness. As a corollary, the canonical MUB is the unique minimal 2-design covariant with respect to the Clifford group except in dimension 3. In addition, these MUBs provide an infinite family of highly symmetric frames and positive-operator-valued measures (POVMs), which are of independent interest.
Rudolf Keller
2004-08-10
In this project, a concept to improve the performance of aluminum production cells by introducing potlining additives was examined and tested. Boron oxide was added to cathode blocks, and titanium was dissolved in the metal pool; this resulted in the formation of titanium diboride and caused the molten aluminum to wet the carbonaceous cathode surface. Such wetting reportedly leads to operational improvements and extended cell life. In addition, boron oxide suppresses cyanide formation. This final report presents and discusses the results of this project. Substantial economic benefits for the practical implementation of the technology are projected, especially for modern cells with graphitized blocks. For example, with an energy savings of about 5% and an increase in pot life from 1500 to 2500 days, a cost savings of $ 0.023 per pound of aluminum produced is projected for a 200 kA pot.
Harrup, Mason K; Rollins, Harry W
2013-11-26
An additive comprising a phosphazene compound that has at least two reactive functional groups and at least one capping functional group bonded to phosphorus atoms of the phosphazene compound. One of the at least two reactive functional groups is configured to react with cellulose and the other of the at least two reactive functional groups is configured to react with a resin, such as an amine resin of a polycarboxylic acid resin. The at least one capping functional group is selected from the group consisting of a short chain ether group, an alkoxy group, or an aryloxy group. Also disclosed are an additive-resin admixture, a method of treating a wood product, and a wood product.
Covariance Matrix Evaluations for Independent Mass Fission Yields
NASA Astrophysics Data System (ADS)
Terranova, N.; Serot, O.; Archier, P.; De Saint Jean, C.; Sumini, M.
2015-01-01
Recent needs for more accurate fission product yields include covariance information to allow improved uncertainty estimations of the parameters used by design codes. The aim of this work is to investigate the possibility to generate more reliable and complete uncertainty information on independent mass fission yields. Mass yields covariances are estimated through a convolution between the multi-Gaussian empirical model based on Brosa's fission modes, which describe the pre-neutron mass yields, and the average prompt neutron multiplicity curve. The covariance generation task has been approached using the Bayesian generalized least squared method through the CONRAD code. Preliminary results on mass yields variance-covariance matrix will be presented and discussed from physical grounds in the case of 235U(nth, f) and 239Pu(nth, f) reactions.
Covariance Matrix Evaluations for Independent Mass Fission Yields
Terranova, N.; Serot, O.; Archier, P.; De Saint Jean, C.
2015-01-15
Recent needs for more accurate fission product yields include covariance information to allow improved uncertainty estimations of the parameters used by design codes. The aim of this work is to investigate the possibility to generate more reliable and complete uncertainty information on independent mass fission yields. Mass yields covariances are estimated through a convolution between the multi-Gaussian empirical model based on Brosa's fission modes, which describe the pre-neutron mass yields, and the average prompt neutron multiplicity curve. The covariance generation task has been approached using the Bayesian generalized least squared method through the CONRAD code. Preliminary results on mass yields variance-covariance matrix will be presented and discussed from physical grounds in the case of {sup 235}U(n{sub th}, f) and {sup 239}Pu(n{sub th}, f) reactions.
True covariance simulation of the EUVE update filter
NASA Technical Reports Server (NTRS)
Bar-Itzhack, Itzhack Y.; Harman, R. R.
1989-01-01
A covariance analysis of the performance and sensitivity of the attitude determination Extended Kalman Filter (EKF) used by the On Board Computer (OBC) of the Extreme Ultra Violet Explorer (EUVE) spacecraft is presented. The linearized dynamics and measurement equations of the error states are derived which constitute the truth model describing the real behavior of the systems involved. The design model used by the OBC EKF is then obtained by reducing the order of the truth model. The covariance matrix of the EKF which uses the reduced order model is not the correct covariance of the EKF estimation error. A true covariance analysis has to be carried out in order to evaluate the correct accuracy of the OBC generated estimates. The results of such analysis are presented which indicate both the performance and the sensitivity of the OBC EKF.
Empirical State Error Covariance Matrix for Batch Estimation
NASA Technical Reports Server (NTRS)
Frisbee, Joe
2015-01-01
State estimation techniques effectively provide mean state estimates. However, the theoretical state error covariance matrices provided as part of these techniques often suffer from a lack of confidence in their ability to describe the uncertainty in the estimated states. By a reinterpretation of the equations involved in the weighted batch least squares algorithm, it is possible to directly arrive at an empirical state error covariance matrix. The proposed empirical state error covariance matrix will contain the effect of all error sources, known or not. This empirical error covariance matrix may be calculated as a side computation for each unique batch solution. Results based on the proposed technique will be presented for a simple, two observer and measurement error only problem.
2013-01-01
Background Intra-specific variation in melanocyte pigmentation, common in the animal kingdom, has caught the eye of naturalists and biologists for centuries. In vertebrates, dark, eumelanin pigmentation is often genetically determined and associated with various behavioral and physiological traits, suggesting that the genes involved in melanism have far reaching pleiotropic effects. The mechanisms linking these traits remain poorly understood, and the potential involvement of developmental processes occurring in the brain early in life has not been investigated. We examined the ontogeny of rapid eye movement (REM) sleep, a state involved in brain development, in a wild population of barn owls (Tyto alba) exhibiting inter-individual variation in melanism and covarying traits. In addition to sleep, we measured melanistic feather spots and the expression of a gene in the feather follicles implicated in melanism (PCSK2). Results As in mammals, REM sleep declined with age across a period of brain development in owlets. In addition, inter-individual variation in REM sleep around this developmental trajectory was predicted by variation in PCSK2 expression in the feather follicles, with individuals expressing higher levels exhibiting a more precocial pattern characterized by less REM sleep. Finally, PCSK2 expression was positively correlated with feather spotting. Conclusions We demonstrate that the pace of brain development, as reflected in age-related changes in REM sleep, covaries with the peripheral activation of the melanocortin system. Given its role in brain development, variation in nestling REM sleep may lead to variation in adult brain organization, and thereby contribute to the behavioral and physiological differences observed between adults expressing different degrees of melanism. PMID:23886007
Measuring evapotranspiration: comparison of eddy covariance, scintillometers and enclosed chambers
NASA Astrophysics Data System (ADS)
Yee, Mei Sun; Beringer, Jason; Pauwels, Valentijn R. N.; Daly, Edoardo; Walker, Jeffrey P.; Rüdiger, Christoph
2014-05-01
satellites such as SMOS, and the NASA SMAP mission. In May 2012, an eddy-covariance system was installed at 16m on top of an 18 m tall tower for the validation of remote sensing products derived by the Japan Aerospace Exploration Agency (JAXA) from data obtained with the Advanced Microwave Scanning Radiometer-2 (AMSR-2) on-board Global Change Observation Mission (GCOM-W1). Using a footprint model, 90% of the fluxes measured by the EC system on the tower are emitted within an approximately 1km footprint upwind of the tower. Two optical (different manufacturers) and two microwave (different frequencies) scintillometers were installed so that their respective footprints were within that of the EC system. Additionally, four automated gas chambers (L:500mm, W:500mm, H:650mm) were deployed in the centre of the ~1km footprint of the EC tower for approximately 8 hours daily, for 3 days a month, from August to December 2013. During the days of the campaigns, further measurements were obtained with a mobile gas chamber (D: 300mm, H: 400mm) within the footprint, at 200m, 400m, 600m and 800m from the tower, along the scintillometer transect. This aims at understanding the spatial variation of evapotranspiration within the ~1km footprint of the EC tower footprint and consequently along the scintillometer path, in order to assess the influence of the individual locations to the overall flux measurements. Results comparing the latent flux measurements derived from the eddy-covariance system, scintillometers, and gas chambers will be presented.
Nonlinear effects in the correlation of tracks and covariance propagation
NASA Astrophysics Data System (ADS)
Sabol, C.; Hill, K.; Alfriend, K.; Sukut, T.
2013-03-01
Even though there are methods for the nonlinear propagation of the covariance the propagation of the covariance in current operational programs is based on the state transition matrix of the 1st variational equations, thus it is a linear propagation. If the measurement errors are zero mean Gaussian, the orbit errors, statistically represented by the covariance, are Gaussian. When the orbit errors become too large they are no longer Gaussian and not represented by the covariance. One use of the covariance is the association of uncorrelated tracks (UCTs). A UCT is an object tracked by a space surveillance system that does not correlate to another object in the space object data base. For an object to be entered into the data base three or more tracks must be correlated. Associating UCTs is a major challenge for a space surveillance system since every object entered into the space object catalog begins as a UCT. It has been proved that if the orbit errors are Gaussian, the error ellipsoid represented by the covariance is the optimum association volume. When the time between tracks becomes large, hours or even days, the orbit errors can become large and are no longer Gaussian, and this has a negative effect on the association of UCTs. This paper further investigates the nonlinear effects on the accuracy of the covariance for use in correlation. The use of the best coordinate system and the unscented Kalman Filter (UKF) for providing a more accurate covariance are investigated along with assessing how these approaches would result in the ability to correlate tracks that are further separated in time.
Are the invariance principles really truly Lorentz covariant?
Arunasalam, V.
1994-02-01
It is shown that some sections of the invariance (or symmetry) principles such as the space reversal symmetry (or parity P) and time reversal symmetry T (of elementary particle and condensed matter physics, etc.) are not really truly Lorentz covariant. Indeed, I find that the Dirac-Wigner sense of Lorentz invariance is not in full compliance with the Einstein-Minkowski reguirements of the Lorentz covariance of all physical laws (i.e., the world space Mach principle).
Large Covariance Estimation by Thresholding Principal Orthogonal Complements
Fan, Jianqing; Liao, Yuan; Mincheva, Martina
2012-01-01
This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented. PMID:24348088
Covariance fitting of highly-correlated data in lattice QCD
NASA Astrophysics Data System (ADS)
Yoon, Boram; Jang, Yong-Chull; Jung, Chulwoo; Lee, Weonjong
2013-07-01
We address a frequently-asked question on the covariance fitting of highly-correlated data such as our B K data based on the SU(2) staggered chiral perturbation theory. Basically, the essence of the problem is that we do not have a fitting function accurate enough to fit extremely precise data. When eigenvalues of the covariance matrix are small, even a tiny error in the fitting function yields a large chi-square value and spoils the fitting procedure. We have applied a number of prescriptions available in the market, such as the cut-off method, modified covariance matrix method, and Bayesian method. We also propose a brand new method, the eigenmode shift (ES) method, which allows a full covariance fitting without modifying the covariance matrix at all. We provide a pedagogical example of data analysis in which the cut-off method manifestly fails in fitting, but the rest work well. In our case of the B K fitting, the diagonal approximation, the cut-off method, the ES method, and the Bayesian method work reasonably well in an engineering sense. However, interpreting the meaning of χ 2 is easier in the case of the ES method and the Bayesian method in a theoretical sense aesthetically. Hence, the ES method can be a useful alternative optional tool to check the systematic error caused by the covariance fitting procedure.
Gaussian covariance matrices for anisotropic galaxy clustering measurements
NASA Astrophysics Data System (ADS)
Grieb, Jan Niklas; Sánchez, Ariel G.; Salazar-Albornoz, Salvador; Dalla Vecchia, Claudio
2016-04-01
Measurements of the redshift-space galaxy clustering have been a prolific source of cosmological information in recent years. Accurate covariance estimates are an essential step for the validation of galaxy clustering models of the redshift-space two-point statistics. Usually, only a limited set of accurate N-body simulations is available. Thus, assessing the data covariance is not possible or only leads to a noisy estimate. Further, relying on simulated realizations of the survey data means that tests of the cosmology dependence of the covariance are expensive. With these points in mind, this work presents a simple theoretical model for the linear covariance of anisotropic galaxy clustering observations with synthetic catalogues. Considering the Legendre moments (`multipoles') of the two-point statistics and projections into wide bins of the line-of-sight parameter (`clustering wedges'), we describe the modelling of the covariance for these anisotropic clustering measurements for galaxy samples with a trivial geometry in the case of a Gaussian approximation of the clustering likelihood. As main result of this paper, we give the explicit formulae for Fourier and configuration space covariance matrices. To validate our model, we create synthetic halo occupation distribution galaxy catalogues by populating the haloes of an ensemble of large-volume N-body simulations. Using linear and non-linear input power spectra, we find very good agreement between the model predictions and the measurements on the synthetic catalogues in the quasi-linear regime.
New capabilities for processing covariance data in resonance region
Wiarda, D.; Dunn, M. E.; Greene, N. M.; Larson, N. M.; Leal, L. C.
2006-07-01
The AMPX [1] code system is a modular system of FORTRAN computer programs that relate to nuclear analysis with a primary emphasis on tasks associated with the production and use of multi group and continuous energy cross sections. The module PUFF-III within this code system handles the creation of multi group covariance data from ENDF information. The resulting covariances are saved in COVERX format [2]. We recently expanded the capabilities of PUFF-III to include full handling of covariance data in the resonance region (resolved as well as unresolved). The new program handles all resonance covariance formats in File 32 except for the long-range covariance sub sections. The new program has been named PUFF-IV. To our knowledge, PUFF-IV is the first processing code that can address both the new ENDF format for resolved resonance parameters and the new ENDF 'compact' covariance format. The existing code base was rewritten in Fortran 90 to allow for a more modular design. Results are identical between the new and old versions within rounding errors, where applicable. Automatic test cases have been added to ensure that consistent results are generated across computer systems. (authors)
The Performance Analysis Based on SAR Sample Covariance Matrix
Erten, Esra
2012-01-01
Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR) context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a combination of them. Due to the inherent speckle phenomenon present in SAR images, the statistical description of the data is almost mandatory for its utilization. The complex images acquired over natural media present in general zero-mean circular Gaussian characteristics. In this case, second order statistics as the multi-channel covariance matrix fully describe the data. For practical situations however, the covariance matrix has to be estimated using a limited number of samples, and this sample covariance matrix follow the complex Wishart distribution. In this context, the eigendecomposition of the multi-channel covariance matrix has been shown in different areas of high relevance regarding the physical properties of the imaged scene. Specifically, the maximum eigenvalue of the covariance matrix has been frequently used in different applications as target or change detection, estimation of the dominant scattering mechanism in polarimetric data, moving target indication, etc. In this paper, the statistical behavior of the maximum eigenvalue derived from the eigendecomposition of the sample multi-channel covariance matrix in terms of multi-channel SAR images is simplified for SAR community. Validation is performed against simulated data and examples of estimation and detection problems using the analytical expressions are as well given. PMID:22736976
Scale covariant gravitation. V - Kinetic theory. VI - Stellar structure and evolution
NASA Technical Reports Server (NTRS)
Hsieh, S.-H.; Canuto, V. M.
1981-01-01
A scale covariant kinetic theory for particles and photons is developed. The mathematical framework of the theory is given by the tangent bundle of a Weyl manifold. The Liouville equation is derived, and solutions to corresponding equilibrium distributions are presented and shown to yield thermodynamic results identical to the ones obtained previously. The scale covariant theory is then used to derive results of interest to stellar structure and evolution. A radiative transfer equation is derived that can be used to study stellar evolution with a variable gravitational constant. In addition, it is shown that the sun's absolute luminosity scales as L approximately equal to GM/kappa, where kappa is the stellar opacity. Finally, a formula is derived for the age of globular clusters as a function of the gravitational constant using a previously derived expression for the absolute luminosity.
Orbit determination covariance analysis for the Deep Space Program Science Experiment mission
NASA Technical Reports Server (NTRS)
Beckman, M.; Yee, C.; Lee, T.; Hoppe, M.; Oza, D.
1993-01-01
To define an appropriate orbit support procedure for the DSPSE mission, detailed permission orbit determination covariance analyses have been performed for the translunar and trans-Geographos mission phases. Preliminary analyses were also performed for the lunar mapping mission phase. These analyses are designed to assess the tracking patterns and the amount of tracking data needed to obtain orbit solutions of required accuracy for each mission phase and before and after each major orbit perturbation, such as orbit maneuvers and flybys of the Earth and Moon. In addition to operational orbit determination procedures, these analyses identify major error sources, estimate their contribution to orbital errors, and address possible strategies to reduce orbit determination error. For the lunar orbit phase, several lunar gravity error modeling approaches have been investigated. The covariance analysis results presented in this paper will serve as a guide for providing orbit determination support for the DSPSE mission.
Increased genetic risk for obesity in premature coronary artery disease
Cole, Christopher B; Nikpay, Majid; Stewart, Alexandre FR; McPherson, Ruth
2016-01-01
There is ongoing controversy as to whether obesity confers risk for CAD independently of associated risk factors including diabetes mellitus. We have carried out a Mendelian randomization study using a genetic risk score (GRS) for body mass index (BMI) based on 35 risk alleles to investigate this question in a population of 5831 early onset CAD cases without diabetes mellitus and 3832 elderly healthy control subjects, all of strictly European ancestry, with adjustment for traditional risk factors (TRFs). We then estimated the genetic correlation between these BMI and CAD (rg) by relating the pairwise genetic similarity matrix to a phenotypic covariance matrix between these two traits. GRSBMI significantly (P=2.12 × 10−12) associated with CAD status in a multivariate model adjusted for TRFs, with a per allele odds ratio (OR) of 1.06 (95% CI 1.042–1.076). The addition of GRSBMI to TRFs explained 0.75% of CAD variance and yielded a continuous net recombination index of 16.54% (95% CI=11.82–21.26%, P<0.0001). To test whether GRSBMI explained CAD status when adjusted for measured BMI, separate models were constructed in which the score and BMI were either included as covariates or not. The addition of BMI explained ~1.9% of CAD variance and GRSBMI plus BMI explained 2.65% of CAD variance. Finally, using bivariate restricted maximum likelihood analysis, we provide strong evidence of genome-wide pleiotropy between obesity and CAD. This analysis supports the hypothesis that obesity is a causal risk factor for CAD. PMID:26220701
Meier, Madeline H; Slutske, Wendy S; Heath, Andrew C; Martin, Nicholas G
2011-05-01
Sex differences in the genetic and environmental influences on childhood conduct disorder and adult antisocial behavior were examined in a large community sample of 6,383 adult male, female, and opposite-sex twins. Retrospective reports of childhood conduct disorder (prior to 18 years of age) were obtained when participants were approximately 30 years old, and lifetime reports of adult antisocial behavior (antisocial behavior after 17 years of age) were obtained 8 years later. Results revealed that either the genetic or the shared environmental factors influencing childhood conduct disorder differed for males and females (i.e., a qualitative sex difference), but by adulthood, these sex-specific influences on antisocial behavior were no longer apparent. Further, genetic and environmental influences accounted for proportionally the same amount of variance in antisocial behavior for males and females in childhood and adulthood (i.e., there were no quantitative sex differences). Additionally, the stability of antisocial behavior from childhood to adulthood was slightly greater for males than females. Though familial factors accounted for more of the stability of antisocial behavior for males than females, genetic factors accounted for the majority of the covariation between childhood conduct disorder and adult antisocial behavior for both sexes. The genetic influences on adult antisocial behavior overlapped completely with the genetic influences on childhood conduct disorder for both males and females. Implications for future twin and molecular genetic studies are discussed. PMID:21319923
Genetic pleiotropy between asthma and obesity in a community-based sample of twins
Hallstrand, Teal S.; Fischer, Mary E.; Wurfel, Mark M.; Afari, Niloofar; Buchwald, Dedra; Goldberg, Jack
2007-01-01
Background Asthma and obesity are common conditions that are strongly associated. This association might be due to shared genetic or environmental causes. Objective We sought to determine whether a shared genetic cause is responsible for the association between asthma and obesity and to estimate the magnitude of shared genetic cause. Methods The analyses were performed with 1001 monozygotic and 383 dizygotic same-sex twin pairs within the University of Washington Twin Registry. The presence of asthma was determined by self-report of a physician diagnosis of asthma, and body mass index (BMI) was calculated by using self-reported height and weight. Obesity was defined as a BMI of 30 or greater. The association between asthma and BMI was assessed by means of mixed-effects ordinal regression. Twin correlations examined the association of asthma and obesity. Univariate and bivariate structural equation models estimated the components of variance attributable to genetic and environmental effects. Results A strong association between asthma and BMI was identified in the sample population (P < .001). Substantial heritability was detected for asthma (53%) and obesity (77%), which is indicative of additive genetic influences on each disorder. The best-fitting model of shared components of variance indicated that 8% of the genetic component of obesity is shared with asthma. Conclusion The covariation between obesity and asthma is predominantly caused by shared genetic risk factors for both conditions. PMID:16337451
Methane fluxes above the Hainich forest by True Eddy Accumulation and Eddy Covariance
NASA Astrophysics Data System (ADS)
Siebicke, Lukas; Gentsch, Lydia; Knohl, Alexander
2016-04-01
Understanding the role of forests for the global methane cycle requires quantifying vegetation-atmosphere exchange of methane, however observations of turbulent methane fluxes remain scarce. Here we measured turbulent fluxes of methane (CH4) above a beech-dominated old-growth forest in the Hainich National Park, Germany, and validated three different measurement approaches: True Eddy Accumulation (TEA, closed-path laser spectroscopy), and eddy covariance (EC, open-path and closed-path laser spectroscopy, respectively). The Hainich flux tower is a long-term Fluxnet and ICOS site with turbulent fluxes and ecosystem observations spanning more than 15 years. The current study is likely the first application of True Eddy Accumulation (TEA) for the measurement of turbulent exchange of methane and one of the very few studies comparing open-path and closed-path eddy covariance (EC) setups side-by-side. We observed uptake of methane by the forest during the day (a methane sink with a maximum rate of 0.03 μmol m‑2 s‑1 at noon) and no or small fluxes of methane from the forest to the atmosphere at night (a methane source of typically less than 0.01 μmol m‑2 s‑1) based on continuous True Eddy Accumulation measurements in September 2015. First results comparing TEA to EC CO2 fluxes suggest that True Eddy Accumulation is a valid option for turbulent flux quantifications using slow response gas analysers (here CRDS laser spectroscopy, other potential techniques include mass spectroscopy). The TEA system was one order of magnitude more energy efficient compared to closed-path eddy covariance. The open-path eddy covariance setup required the least amount of user interaction but is often constrained by low signal-to-noise ratios obtained when measuring methane fluxes over forests. Closed-path eddy covariance showed good signal-to-noise ratios in the lab, however in the field it required significant amounts of user intervention in addition to a high power consumption. We
New cyberinfrastructure for studying land-atmosphere interactions using eddy covariance techniques
NASA Astrophysics Data System (ADS)
Jaimes, A.; Salayandia, L.; Gallegos, I.; Gates, A. Q.; Tweedie, C.
2010-12-01
limitations on ecological instrumentation output that affect data uncertainty. The objective was to parameterize and capture scientific knowledge necessary to typify data quality associated with eddy covariance methods. The process was documented by developing workflow driven ontologies, which can be used to disseminate how the Eddy Covariance Data is being captured and processed at JER, and also to automate the capture of provenance meta-data. Ultimately, we hope to develop scalable Eddy Covariance data capturing systems that offer additional information about how the data was captured, which hopefully will result in data sets with a higher degree of re-usability.
Genetics and behavior: a guide for practitioners.
Overall, Karen L; Tiira, Katriina; Broach, Desiree; Bryant, Deborah
2014-05-01
Phenotyping behavior is difficult, partly because behavior is almost always influenced by environment. Using objective terms/criteria to evaluate behaviors is best; the more objective the assessment, the more likely underlying genetic patterns will be identified. Behavioral pathologies, and highly desirable behavioral characteristics/traits, are likely complex, meaning that multiple genes are probably involved, and therefore simple genetic tests are less possible. Breeds can be improved using traditional quantitative genetic methods; unfortunately, this also creates the possibility of inadvertently selecting for covarying undesirable behaviors. Patterns of behaviors within families and breed lines are still the best guidelines for genetic counseling in dogs. PMID:24766696
An Empirical State Error Covariance Matrix for Batch State Estimation
NASA Technical Reports Server (NTRS)
Frisbee, Joseph H., Jr.
2011-01-01
State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. Consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. It then follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully account for the error in the state estimate. By way of a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm, it is possible to arrive at an appropriate, and formally correct, empirical state error covariance matrix. The first specific step of the method is to use the average form of the weighted measurement residual variance performance index rather than its usual total weighted residual form. Next it is helpful to interpret the solution to the normal equations as the average of a collection of sample vectors drawn from a hypothetical parent population. From here, using a standard statistical analysis approach, it directly follows as to how to determine the standard empirical state error covariance matrix. This matrix will contain the total uncertainty in the
ERIC Educational Resources Information Center
Paloyelis, Yannis; Rijsdijk, Fruhling; Wood, Alexis C.; Asherson, Philip; Kuntsi, Jonna
2010-01-01
Previous studies have documented the primarily genetic aetiology for the stronger phenotypic covariance between reading disability and ADHD inattention symptoms, compared to hyperactivity-impulsivity symptoms. In this study, we examined to what extent this covariation could be attributed to "generalist genes" shared with general cognitive ability…
Shrinkage Estimation of Varying Covariate Effects Based On Quantile Regression
Peng, Limin; Xu, Jinfeng; Kutner, Nancy
2013-01-01
Varying covariate effects often manifest meaningful heterogeneity in covariate-response associations. In this paper, we adopt a quantile regression model that assumes linearity at a continuous range of quantile levels as a tool to explore such data dynamics. The consideration of potential non-constancy of covariate effects necessitates a new perspective for variable selection, which, under the assumed quantile regression model, is to retain variables that have effects on all quantiles of interest as well as those that influence only part of quantiles considered. Current work on l1-penalized quantile regression either does not concern varying covariate effects or may not produce consistent variable selection in the presence of covariates with partial effects, a practical scenario of interest. In this work, we propose a shrinkage approach by adopting a novel uniform adaptive LASSO penalty. The new approach enjoys easy implementation without requiring smoothing. Moreover, it can consistently identify the true model (uniformly across quantiles) and achieve the oracle estimation efficiency. We further extend the proposed shrinkage method to the case where responses are subject to random right censoring. Numerical studies confirm the theoretical results and support the utility of our proposals. PMID:25332515
Covariant Lyapunov vectors of chaotic Rayleigh-Bénard convection
NASA Astrophysics Data System (ADS)
Xu, M.; Paul, M. R.
2016-06-01
We explore numerically the high-dimensional spatiotemporal chaos of Rayleigh-Bénard convection using covariant Lyapunov vectors. We integrate the three-dimensional and time-dependent Boussinesq equations for a convection layer in a shallow square box geometry with an aspect ratio of 16 for very long times and for a range of Rayleigh numbers. We simultaneously integrate many copies of the tangent space equations in order to compute the covariant Lyapunov vectors. The dynamics explored has fractal dimensions of 20 ≲Dλ≲50 , and we compute on the order of 150 covariant Lyapunov vectors. We use the covariant Lyapunov vectors to quantify the degree of hyperbolicity of the dynamics and the degree of Oseledets splitting and to explore the temporal and spatial dynamics of the Lyapunov vectors. Our results indicate that the chaotic dynamics of Rayleigh-Bénard convection is nonhyperbolic for all of the Rayleigh numbers we have explored. Our results yield that the entire spectrum of covariant Lyapunov vectors that we have computed are tangled as indicated by near tangencies with neighboring vectors. A closer look at the spatiotemporal features of the Lyapunov vectors suggests contributions from structures at two different length scales with differing amounts of localization.
Covariant Lyapunov vectors of chaotic Rayleigh-Bénard convection.
Xu, M; Paul, M R
2016-06-01
We explore numerically the high-dimensional spatiotemporal chaos of Rayleigh-Bénard convection using covariant Lyapunov vectors. We integrate the three-dimensional and time-dependent Boussinesq equations for a convection layer in a shallow square box geometry with an aspect ratio of 16 for very long times and for a range of Rayleigh numbers. We simultaneously integrate many copies of the tangent space equations in order to compute the covariant Lyapunov vectors. The dynamics explored has fractal dimensions of 20≲D_{λ}≲50, and we compute on the order of 150 covariant Lyapunov vectors. We use the covariant Lyapunov vectors to quantify the degree of hyperbolicity of the dynamics and the degree of Oseledets splitting and to explore the temporal and spatial dynamics of the Lyapunov vectors. Our results indicate that the chaotic dynamics of Rayleigh-Bénard convection is nonhyperbolic for all of the Rayleigh numbers we have explored. Our results yield that the entire spectrum of covariant Lyapunov vectors that we have computed are tangled as indicated by near tangencies with neighboring vectors. A closer look at the spatiotemporal features of the Lyapunov vectors suggests contributions from structures at two different length scales with differing amounts of localization. PMID:27415256
Covariate-adjusted confidence interval for the intraclass correlation coefficient.
Shoukri, Mohamed M; Donner, Allan; El-Dali, Abdelmoneim
2013-09-01
A crucial step in designing a new study is to estimate the required sample size. For a design involving cluster sampling, the appropriate sample size depends on the so-called design effect, which is a function of the average cluster size and the intracluster correlation coefficient (ICC). It is well-known that under the framework of hierarchical and generalized linear models, a reduction in residual error may be achieved by including risk factors as covariates. In this paper we show that the covariate design, indicating whether the covariates are measured at the cluster level or at the within-cluster subject level affects the estimation of the ICC, and hence the design effect. Therefore, the distinction between these two types of covariates should be made at the design stage. In this paper we use the nested-bootstrap method to assess the accuracy of the estimated ICC for continuous and binary response variables under different covariate structures. The codes of two SAS macros are made available by the authors for interested readers to facilitate the construction of confidence intervals for the ICC. Moreover, using Monte Carlo simulations we evaluate the relative efficiency of the estimators and evaluate the accuracy of the coverage probabilities of a 95% confidence interval on the population ICC. The methodology is illustrated using a published data set of blood pressure measurements taken on family members. PMID:23871746
Manifestly covariant Jüttner distribution and equipartition theorem
NASA Astrophysics Data System (ADS)
Chacón-Acosta, Guillermo; Dagdug, Leonardo; Morales-Técotl, Hugo A.
2010-02-01
The relativistic equilibrium velocity distribution plays a key role in describing several high-energy and astrophysical effects. Recently, computer simulations favored Jüttner’s as the relativistic generalization of Maxwell’s distribution for d=1,2,3 spatial dimensions and pointed to an invariant temperature. In this work, we argue an invariant temperature naturally follows from manifest covariance. We present a derivation of the manifestly covariant Jüttner’s distribution and equipartition theorem. The standard procedure to get the equilibrium distribution as a solution of the relativistic Boltzmann’s equation, which holds for dilute gases, is here adopted. However, contrary to previous analysis, we use Cartesian coordinates in d+1 momentum space, with d spatial components. The use of the multiplication theorem of Bessel functions turns crucial to regain the known invariant form of Jüttner’s distribution. Since equilibrium kinetic-theory results should agree with thermodynamics in the comoving frame to the gas the covariant pseudonorm of a vector entering the distribution can be identified with the reciprocal of temperature in such comoving frame. Then by combining the covariant statistical moments of Jüttner’s distribution a form of the equipartition theorem is advanced which also accommodates the invariant comoving temperature and it contains, as a particular case, a previous not manifestly covariant form.
Wang, Yuanjia
2011-01-01
Longitudinal data are routinely collected in biomedical research studies. A natural model describing longitudinal data decomposes an individual’s outcome as the sum of a population mean function and random subject-specific deviations. When parametric assumptions are too restrictive, methods modeling the population mean function and the random subject-specific functions nonparametrically are in demand. In some applications, it is desirable to estimate a covariance function of random subject-specific deviations. In this work, flexible yet computationally efficient methods are developed for a general class of semiparametric mixed effects models, where the functional forms of the population mean and the subject-specific curves are unspecified. We estimate nonparametric components of the model by penalized spline (P-spline, [1]), and reparametrize the random curve covariance function by a modified Cholesky decomposition [2] which allows for unconstrained estimation of a positive semidefinite matrix. To provide smooth estimates, we penalize roughness of fitted curves and derive closed form solutions in the maximization step of an EM algorithm. In addition, we present models and methods for longitudinal family data where subjects in a family are correlated and we decompose the covariance function into a subject-level source and observation-level source. We apply these methods to the multi-level Framingham Heart Study data to estimate age-specific heritability of systolic blood pressure (SBP) nonparametrically. PMID:21491474
You, Jinhong; Zhou, Haibo
2009-01-01
We consider statistical inference on a regression model in which some covariables are measured with errors together with an auxiliary variable. The proposed estimation for the regression coefficients is based on some estimating equations. This new method alleates some drawbacks of previously proposed estimations. This includes the requirment of undersmoothing the regressor functions over the auxiliary variable, the restriction on other covariables which can be observed exactly, among others. The large sample properties of the proposed estimator are established. We further propose a jackknife estimation, which consists of deleting one estimating equation (instead of one obervation) at a time. We show that the jackknife estimator of the regression coefficients and the estimating equations based estimator are asymptotically equivalent. Simulations show that the jackknife estimator has smaller biases when sample size is small or moderate. In addition, the jackknife estimation can also provide a consistent estimator of the asymptotic covariance matrix, which is robust to the heteroscedasticity. We illustrate these methods by applying them to a real data set from marketing science. PMID:22199460
NASA Astrophysics Data System (ADS)
Wlasak, M. A.; Cullen, M. J. P.
2014-06-01
A major difference in the formulation of the univariate part of static background error covariance models for use in global operational 4DVAR arises from the order in which the horizontal and vertical transforms are applied. This is because the atmosphere is non-separable with large horizontal scales generally tied to large vertical scales and small horizontal scales tied to small vertical scales. Also horizontal length scales increase dramatically as one enters the stratosphere. A study is presented which evaluates the strengths and weaknesses of each approach with the Met Office Unified Model. It is shown that if the vertical transform is applied as a function of horizontal wavenumber then the horizontal globally-averaged variance and the homogenous, isotropic length scale on each model level for each control variable of the training data is preserved by the covariance model. In addition the wind variance and associated length scales are preserved as the scheme preserves the variances and length scales of horizontal derivatives. If the vertical transform is applied in physical space, it is possible to make it a function of latitude at the cost of not preserving the variances and length scales of the horizontal derivatives. Summer and winter global 4DVAR trials have been run with both background error covariance models. A clear benefit is seen in the fit to observations when the vertical transform is in spectral space and is a function of total horizontal wavenumber.
Lailvaux, Simon P; Hall, Matthew D; Brooks, Robert C
2010-05-01
The genetic relationships among traits contributing to overall fitness are an important subject of inquiry because such relationships influence how suites of traits respond to selection. Within the field of sexual selection, these relationships are also of interest for assessing whether any given trait can be used as a proxy for total fitness. A growing number of studies have demonstrated close links between whole-organism performance traits and determinants of individual fitness; however, an understanding of the genetic relationships between performance and important aspects of genetic quality is currently lacking. We present the results of a quantitative genetic study in which we estimate covariation between a locomotor performance trait (maximal jumping ability), calling effort, sexual attractiveness, and life-history traits in male Teleogryllus commodus crickets. We show that the major axis of genetic variation (gmax) is characterized by a contrast between jump performance and life-history traits associated with mating success. Moreover, two additional axes of significant multivariate genetic variation exist, each characterized by strong contrasts among traits. These results argue against the existence of a single axis representing genetic quality, favoring instead the idea that resource allocation strategies shape multiple dimensions of genetic quality through trade-offs among key life-history traits, including performance. PMID:20503884
Genetic Variability of Show Jumping Attributes in Young Horses Commencing Competing
Próchniak, Tomasz; Rozempolska-Rucińska, Iwona; Zięba, Grzegorz; Łukaszewicz, Marek
2015-01-01
The aim of the study was to select traits that may constitute a prospective criterion for breeding value prediction of young horses. The results of 1,232 starts of 894 four-, five-, six-, and seven-year-old horses, obtained during jumping championships for young horses which had not been evaluated in, alternative to championships, training centres were analyed. Nine traits were chosen of those recorded: ranking in the championship, elimination (y/n), conformation, rating of style on day one, two, and three, and penalty points on day one, two, and three of a championship. (Co)variance components were estimated via the Gibbs sampling procedure and adequate (co)variance component ratios were calculated. Statistical classifications were trait dependent but all fitted random additive genetic and permanent environment effects. It was found that such characteristics as penalty points and jumping style are potential indicators of jumping ability, and the genetic variability of the traits was within the range of 14% to 27%. Given the low genetic correlations between the conformation and other results achieved on the parkour, the relevance of assessment of conformation in four-years-old horses has been questioned. PMID:26104516
Genetic Variability of Show Jumping Attributes in Young Horses Commencing Competing.
Próchniak, Tomasz; Rozempolska-Rucińska, Iwona; Zięba, Grzegorz; Łukaszewicz, Marek
2015-08-01
The aim of the study was to select traits that may constitute a prospective criterion for breeding value prediction of young horses. The results of 1,232 starts of 894 four-, five-, six-, and seven-year-old horses, obtained during jumping championships for young horses which had not been evaluated in, alternative to championships, training centres were analyed. Nine traits were chosen of those recorded: ranking in the championship, elimination (y/n), conformation, rating of style on day one, two, and three, and penalty points on day one, two, and three of a championship. (Co)variance components were estimated via the Gibbs sampling procedure and adequate (co)variance component ratios were calculated. Statistical classifications were trait dependent but all fitted random additive genetic and permanent environment effects. It was found that such characteristics as penalty points and jumping style are potential indicators of jumping ability, and the genetic variability of the traits was within the range of 14% to 27%. Given the low genetic correlations between the conformation and other results achieved on the parkour, the relevance of assessment of conformation in four-years-old horses has been questioned. PMID:26104516
Estimates of genetic parameters for direct and maternal effects on embryonic survival in swine.
Gama, L T; Boldman, K G; Johnson, R K
1991-12-01
Survival of 16,838 potential embryos was determined by counting corpora lutea and fetuses at 50 d of gestation for 1,081 litters by 225 sires. These data, coded as 1 or 0 depending on whether an ovulation was represented by a fetus, were used to estimate direct and maternal additive genetic variances and their covariance for embryonic survival. Data were from first-parity gilts of a Large White-Landrace composite population subdivided into two lines, one selected for an index of ovulation rate and embryonic survival for seven generations and a contemporary control line. Variance components were obtained by ANOVA and expectations of covariances among relatives and by derivative-free restricted maximum likelihood (DFREML) in an animal model. As a trait of the embryo, heritability of direct effects obtained with ANOVA was 3.8%, heritability of maternal effects was 1.5%, and the genetic correlation between them was -.51. After adjustment of embryonic survival for ovulation rate, lower estimates of each parameter were obtained with ANOVA. Heritability of embryonic survival as a trait of the dam was 9 to 10%. Estimates of heritability of both direct and maternal effects obtained with DFREML were less than 1% and the genetic correlation between them was -.64. When survival of embryos from only those dams with 15 or more ovulations was analyzed, heritability of maternal effects was 4.4%. Estimates of common environmental effects on embryonic survival ranged from 5 to 7%. PMID:1808176
Regional Scaling of Airborne Eddy Covariance Flux Observation
NASA Astrophysics Data System (ADS)
Sachs, T.; Serafimovich, A.; Metzger, S.; Kohnert, K.; Hartmann, J.
2014-12-01
The earth's surface is tightly coupled to the global climate system by the vertical exchange of energy and matter. Thus, to better understand and potentially predict changes to our climate system, it is critical to quantify the surface-atmosphere exchange of heat, water vapor, and greenhouse gases on climate-relevant spatial and temporal scales. Currently, most flux observations consist of ground-based, continuous but local measurements. These provide a good basis for temporal integration, but may not be representative of the larger regional context. This is particularly true for the Arctic, where site selection is additionally bound by logistical constraints, among others. Airborne measurements can overcome this limitation by covering distances of hundreds of kilometers over time periods of a few hours. The Airborne Measurements of Methane Fluxes (AIRMETH) campaigns are designed to quantitatively and spatially explicitly address this issue: The research aircraft POLAR 5 is used to acquire thousands of kilometers of eddy-covariance flux data. During the AIRMETH-2012 and AIRMETH-2013 campaigns we measured the turbulent exchange of energy, methane, and (in 2013) carbon dioxide over the North Slope of Alaska, USA, and the Mackenzie Delta, Canada. Here, we present the potential of environmental response functions (ERFs) for quantitatively linking flux observations to meteorological and biophysical drivers in the flux footprints. We use wavelet transforms of the original high-frequency data to improve spatial discretization of the flux observations. This also enables the quantification of continuous and biophysically relevant land cover properties in the flux footprint of each observation. A machine learning technique is then employed to extract and quantify the functional relationships between flux observations and the meteorological and biophysical drivers. The resulting ERFs are used to extrapolate fluxes over spatio-temporally explicit grids of the study area. The
Mass, charge, and motion in covariant gravity theories
NASA Astrophysics Data System (ADS)
Gralla, Samuel E.
2013-05-01
Previous work established a universal form for the equation of motion of small bodies in theories of a metric and other tensor fields that have second-order field equations following from a covariant Lagrangian in four spacetime dimensions. Differences in the motion of the “same” body in two different theories are entirely accounted for by differences in the body’s effective mass and charges in those different theories. Previously the process of computing the mass and charges for a particular body was left implicit, to be determined in each particular theory as the need arises. I now obtain explicit expressions for the mass and charges of a body as surface integrals of the fields it generates, where the integrand is constructed from the symplectic current for the theory. This allows the entire prescription for computing the motion of a small body to be written down in a few lines, in a manner universal across bodies and theories. For simplicity I restrict to scalar and vector fields (in addition to the metric), but there is no obstacle to treating higher-rank tensor fields. I explicitly apply the prescription to work out specific equations for various body types in Einstein gravity, generalized Brans-Dicke theory (in both Jordan and Einstein frames), Einstein-Maxwell theory and the Will-Nordvedt vector-tensor theory. In the scalar-tensor case, this clarifies the origin and meaning of the “sensitivities” defined by Eardley and others, and provides explicit formulas for their evaluation.
Eddy covariance for quantifying trace gas fluxes from soils
NASA Astrophysics Data System (ADS)
Eugster, W.; Merbold, L.
2015-02-01
Soils are highly complex physical and biological systems, and hence measuring soil gas exchange fluxes with high accuracy and adequate spatial representativity remains a challenge. A technique which has become increasingly popular is the eddy covariance (EC) method. This method takes advantage of the fact that surface fluxes are mixed into the near-surface atmosphere via turbulence. As a consequence, measurements with an EC system can be done at some distance above the surface, providing accurate and spatially integrated flux density estimates. In this paper we provide a basic overview targeting scientists who are not familiar with the EC method. This review gives examples of successful deployments from a wide variety of ecosystems. The primary focus is on the three major greenhouse gases: carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Several limitations to the application of EC systems exist, requiring a careful experimental design, which we discuss in detail. Thereby we group these experiments into two main classes: (1) manipulative experiments, and (2) survey-type experiments. Recommendations and examples of successful studies using various approaches are given, including the combination of EC flux measurements with online measurements of stable isotopes. We conclude that EC should not be considered a substitute to traditional (e.g., chamber based) flux measurements but instead an addition to them. The greatest strength of EC measurements in soil science are (1) their uninterrupted continuous measurement of gas concentrations and fluxes that can also capture short-term bursts of fluxes that easily could be missed by other methods and (2) the spatial integration covering the ecosystem scale (several square meters to hectares), thereby integrating over small-scale heterogeneity in the soil.
Eddy covariance for quantifying trace gas fluxes from soils
NASA Astrophysics Data System (ADS)
Eugster, W.; Merbold, L.
2014-10-01
Soils are highly complex physical and biological systems, and hence measuring soil gas exchange fluxes with high accuracy and adequate spatial representativity remains a challenge. A technique which has become increasingly popular is the eddy covariance (EC) method. This method takes advantage of the fact that surface fluxes are mixed into the near-surface atmosphere via turbulence. As a consequence, measurement with an EC system can be done at some distance above the surface, providing accurate and spatially integrated flux density estimates. In this paper we provide a basic overview targeting at scientists who are not familiar with the EC method. This reviews gives examples of successful deployments from a wide variety of ecosystems. The primary focus is on the three major greenhouse gases carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Several limitations to the application of EC systems exist, requiring a careful experimental design, which we discuss in detail. Thereby we group these experiments into two main classes: (1) manipulative experiments, and (2) survey-type experiments. Recommendations and examples of successful studies using various approaches, including the combination of EC flux measurements with online measurements of stable isotopes are given. We conclude that EC should not be considered a substitution of traditional flux measurements, but an addition to the latter. The greatest strength of EC measurements in soil science are (1) their uninterrupted continuous measurement of gas concentrations and fluxes that also can capture short-term bursts of fluxes that easily could be missed by other methods; and (2) the spatial integration covering the ecosystem scale (several m2 to ha), thereby integrating over small-scale heterogeneity in the soil.
Revised error propagation of 40Ar/39Ar data, including covariances
NASA Astrophysics Data System (ADS)
Vermeesch, Pieter
2015-12-01
The main advantage of the 40Ar/39Ar method over conventional K-Ar dating is that it does not depend on any absolute abundance or concentration measurements, but only uses the relative ratios between five isotopes of the same element -argon- which can be measured with great precision on a noble gas mass spectrometer. The relative abundances of the argon isotopes are subject to a constant sum constraint, which imposes a covariant structure on the data: the relative amount of any of the five isotopes can always be obtained from that of the other four. Thus, the 40Ar/39Ar method is a classic example of a 'compositional data problem'. In addition to the constant sum constraint, covariances are introduced by a host of other processes, including data acquisition, blank correction, detector calibration, mass fractionation, decay correction, interference correction, atmospheric argon correction, interpolation of the irradiation parameter, and age calculation. The myriad of correlated errors arising during the data reduction are best handled by casting the 40Ar/39Ar data reduction protocol in a matrix form. The completely revised workflow presented in this paper is implemented in a new software platform, Ar-Ar_Redux, which takes raw mass spectrometer data as input and generates accurate 40Ar/39Ar ages and their (co-)variances as output. Ar-Ar_Redux accounts for all sources of analytical uncertainty, including those associated with decay constants and the air ratio. Knowing the covariance matrix of the ages removes the need to consider 'internal' and 'external' uncertainties separately when calculating (weighted) mean ages. Ar-Ar_Redux is built on the same principles as its sibling program in the U-Pb community (U-Pb_Redux), thus improving the intercomparability of the two methods with tangible benefits to the accuracy of the geologic time scale. The program can be downloaded free of charge from
Spatial covariation of local abundance among different parasite species: the effect of shared hosts.
Lagrue, C; Poulin, R
2015-10-01
Within any parasite species, abundance varies spatially, reaching higher values in certain localities than in others, presumably reflecting the local availability of host resources or the local suitability of habitat characteristics for free-living stages. In the absence of strong interactions between two species of helminths with complex life cycles, we might predict that the degree to which their abundances covary spatially is determined by their common resource requirements, i.e. how many host species they share throughout their life cycles. We test this prediction using five trematode species, all with a typical three-host cycle, from multiple lake sampling sites in New Zealand's South Island: Stegodexamene anguillae, Telogaster opisthorchis, Coitocaecum parvum, Maritrema poulini, and an Apatemon sp. Pairs of species from this set of five share the same host species at either one, two, or all three life cycle stages. Our results show that when two trematode species share the same host species at all three life stages, they show positive spatial covariation in abundance (of metacercarial and adult stages) across localities. When they share hosts at two life stages, they show positive spatial covariation in abundance in some cases but not others. Finally, if two trematode species share only one host species, at a single life stage, their abundances do not covary spatially. These findings indicate that the extent of resource sharing between parasite species can drive the spatial match-mismatch between their abundances, and thus influence their coevolutionary dynamics and the degree to which host populations suffer from additive or synergistic effects of multiple infections. PMID:26113509
Bertipaglia, T S; Carreño, L O D; Aspilcueta-Borquis, R R; Boligon, A A; Farah, M M; Gomes, F J; Machado, C H C; Rey, F S B; da Fonseca, R
2015-08-01
Random regression models (RRM) and multitrait models (MTM) were used to estimate genetic parameters for growth traits in Brazilian Brahman cattle and to compare the estimated breeding values obtained by these 2 methodologies. For RRM, 78,641 weight records taken between 60 and 550 d of age from 16,204 cattle were analyzed, and for MTM, the analysis consisted of 17,385 weight records taken at the same ages from 12,925 cattle. All models included the fixed effects of contemporary group and the additive genetic, maternal genetic, and animal permanent environmental effects and the quadratic effect of age at calving (AAC) as covariate. For RRM, the AAC was nested in the animal's age class. The best RRM considered cubic polynomials and the residual variance heterogeneity (5 levels). For MTM, the weights were adjusted for standard ages. For RRM, additive heritability estimates ranged from 0.42 to 0.75, and for MTM, the estimates ranged from 0.44 to 0.72 for both models at 60, 120, 205, 365, and 550 d of age. The maximum maternal heritability estimate (0.08) was at 140 d for RRM, but for MTM, it was highest at weaning (0.09). The magnitude of the genetic correlations was generally from moderate to high. The RRM adequately modeled changes in variance or covariance with age, and provided there was sufficient number of samples, increased accuracy in the estimation of the genetic parameters can be expected. Correlation of bull classifications were different in both methods and at all the ages evaluated, especially at high selection intensities, which could affect the response to selection. PMID:26440161
[Genetics and genetic counseling].
Izzi, Claudia; Liut, Francesca; Dallera, Nadia; Mazza, Cinzia; Magistroni, Riccardo; Savoldi, Gianfranco; Scolari, Francesco
2016-01-01
Autosomal Dominant Polycystic Kidney Disease (ADPKD) is the most frequent genetic disease, characterized by progressive development of bilateral renal cysts. Two causative genes have been identified: PKD1 and PKD2. ADPKD phenotype is highly variable. Typically, ADPKD is an adult onset disease. However, occasionally, ADPKD manifests as very early onset disease. The phenotypic variability of ADPKD can be explained at three genetic levels: genic, allelic and gene modifier effects. Recent advances in molecular screening for PKD gene mutations and the introduction of the new next generation sequencing (NGS)- based genotyping approach have generated considerable improvement regarding the knowledge of genetic basis of ADPKD. The purpose of this article is to provide a comprehensive review of the genetics of ADPKD, focusing on new insights in genotype-phenotype correlation and exploring novel clinical approach to genetic testing. Evaluation of these new genetic information requires a multidisciplinary approach involving a nephrologist and a clinical geneticist. PMID:27067213
Addressing spectroscopic quality of covariant density functional theory
NASA Astrophysics Data System (ADS)
Afanasjev, A. V.
2015-03-01
The spectroscopic quality of covariant density functional theory has been accessed by analyzing the accuracy and theoretical uncertainties in the description of spectroscopic observables. Such analysis is first presented for the energies of the single-particle states in spherical and deformed nuclei. It is also shown that the inclusion of particle-vibration coupling improves the description of the energies of predominantly single-particle states in medium and heavy-mass spherical nuclei. However, the remaining differences between theory and experiment clearly indicate missing physics and missing terms in covariant energy density functionals. The uncertainties in the predictions of the position of two-neutron drip line sensitively depend on the uncertainties in the prediction of the energies of the single-particle states. On the other hand, many spectroscopic observables in well deformed nuclei at ground state and finite spin only weakly depend on the choice of covariant energy density functional.
Effects of Nicotine Deprivation on Craving Response Covariation in Smokers
Sayette, Michael A.; Martin, Christopher S.; Hull, Jay G.; Wertz, Joan M.; Perrott, Michael A.
2009-01-01
Most models of craving propose that when cravings are strong, diverse responses—thought to index an underlying craving state— covary. Previous studies provided weak support for this hypothesis. The authors tested whether nicotine deprivation affects degree of covariation across multiple measures related to craving. Heavy and light smokers (N = 127) were exposed to smoking cues while either nicotine deprived or nondeprived. Measures included urge ratings, affective valence, a behavioral choice task assessing perceived reinforcement value of smoking, and smoking-related judgment tasks. Results indicated higher correlations in the nicotine-deprived than in nondeprived group. The measures principally responsible for this effect loaded onto a single common Craving factor for nicotine-deprived but not nondeprived smokers. These findings suggest that, under certain conditions, measures of craving-related processes covary. PMID:12653419
Realistic Covariance Prediction for the Earth Science Constellation
NASA Technical Reports Server (NTRS)
Duncan, Matthew; Long, Anne
2006-01-01
Routine satellite operations for the Earth Science Constellation (ESC) include collision risk assessment between members of the constellation and other orbiting space objects. One component of the risk assessment process is computing the collision probability between two space objects. The collision probability is computed using Monte Carlo techniques as well as by numerically integrating relative state probability density functions. Each algorithm takes as inputs state vector and state vector uncertainty information for both objects. The state vector uncertainty information is expressed in terms of a covariance matrix. The collision probability computation is only as good as the inputs. Therefore, to obtain a collision calculation that is a useful decision-making metric, realistic covariance matrices must be used as inputs to the calculation. This paper describes the process used by the NASA/Goddard Space Flight Center's Earth Science Mission Operations Project to generate realistic covariance predictions for three of the Earth Science Constellation satellites: Aqua, Aura and Terra.
Realistic Covariance Prediction For the Earth Science Constellations
NASA Technical Reports Server (NTRS)
Duncan, Matthew; Long, Anne
2006-01-01
Routine satellite operations for the Earth Science Constellations (ESC) include collision risk assessment between members of the constellations and other orbiting space objects. One component of the risk assessment process is computing the collision probability between two space objects. The collision probability is computed via Monte Carlo techniques as well as numerically integrating relative probability density functions. Each algorithm takes as inputs state vector and state vector uncertainty information for both objects. The state vector uncertainty information is expressed in terms of a covariance matrix. The collision probability computation is only as good as the inputs. Therefore, to obtain a collision calculation that is a useful decision-making metric, realistic covariance matrices must be used as inputs to the calculation. This paper describes the process used by NASA Goddard's Earth Science Mission Operations Project to generate realistic covariance predictions for three of the ESC satellites: Aqua, Aura, and Terra
Data Covariances from R-Matrix Analyses of Light Nuclei
Hale, G.M. Paris, M.W.
2015-01-15
After first reviewing the parametric description of light-element reactions in multichannel systems using R-matrix theory and features of the general LANL R-matrix analysis code EDA, we describe how its chi-square minimization procedure gives parameter covariances. This information is used, together with analytically calculated sensitivity derivatives, to obtain cross section covariances for all reactions included in the analysis by first-order error propagation. Examples are given of the covariances obtained for systems with few resonances ({sup 5}He) and with many resonances ({sup 13}C ). We discuss the prevalent problem of this method leading to cross section uncertainty estimates that are unreasonably small for large data sets. The answer to this problem appears to be using parameter confidence intervals in place of standard errors.
Quasi-local mass in the covariant Newtonian spacetime
NASA Astrophysics Data System (ADS)
Wu, Yu-Huei; Wang, Chih-Hung
2008-07-01
In general relativity, quasi-local energy momentum expressions have been constructed from various formulae. However, the Newtonian theory of gravity gives a well-known and a unique quasi-local mass expression (surface integration). Since geometrical formulation of Newtonian gravity has been established in the covariant Newtonian spacetime, it provides a covariant approximation from relativistic to Newtonian theories. By using this approximation, we calculate the Komar integral, the Brown York quasi-local energy and the Dougan Mason quasi-local mass in the covariant Newtonian spacetime. It turns out that the Komar integral naturally gives the Newtonian quasi-local mass expression; however, further conditions (spherical symmetry) need to be made for Brown York and Dougan Mason expressions.
Adaptive Covariance Inflation in a Multi-Resolution Assimilation Scheme
NASA Astrophysics Data System (ADS)
Hickmann, K. S.; Godinez, H. C.
2015-12-01
When forecasts are performed using modern data assimilation methods observation and model error can be scaledependent. During data assimilation the blending of error across scales can result in model divergence since largeerrors at one scale can be propagated across scales during the analysis step. Wavelet based multi-resolution analysiscan be used to separate scales in model and observations during the application of an ensemble Kalman filter. However,this separation is done at the cost of implementing an ensemble Kalman filter at each scale. This presents problemswhen tuning the covariance inflation parameter at each scale. We present a method to adaptively tune a scale dependentcovariance inflation vector based on balancing the covariance of the innovation and the covariance of observations ofthe ensemble. Our methods are demonstrated on a one dimensional Kuramoto-Sivashinsky (K-S) model known todemonstrate non-linear interactions between scales.
Covariant electromagnetic theory for inertial frames with substratum flow
NASA Astrophysics Data System (ADS)
Wilhelm, H. E.
1985-10-01
The original Maxwell's equations for the ether rest frame are generalized to electromagnetic field equations for arbitrary inertial frames in which the ether is in a state of motion. The electromagnetic field equations with ether flow w are found to be Galilei covariant, and reduce to the Maxwell equations in the limit w/c goes to zero. Electromagnetic signals propagate isotropically with the speed of light relative to the ether. Relative to inertial frames with ether flow w, electromagnetic signals propagate anisotropically. In inertial frames with ether flow, an electromagnetic wave experiences a blue or red shift. The difficulties of the Lorentz covariant and ether-free special theory of relativity are removed by adopting a covariance principle compatible with an electromagnetic ether. The present theory is shown to agree with the Michelson-Morley and Doppler effect experiment.
Data Covariances from R-Matrix Analyses of Light Nuclei
NASA Astrophysics Data System (ADS)
Hale, G. M.; Paris, M. W.
2015-01-01
After first reviewing the parametric description of light-element reactions in multichannel systems using R-matrix theory and features of the general LANL R-matrix analysis code EDA, we describe how its chi-square minimization procedure gives parameter covariances. This information is used, together with analytically calculated sensitivity derivatives, to obtain cross section covariances for all reactions included in the analysis by first-order error propagation. Examples are given of the covariances obtained for systems with few resonances (5He) and with many resonances (13C). We discuss the prevalent problem of this method leading to cross section uncertainty estimates that are unreasonably small for large data sets. The answer to this problem appears to be using parameter confidence intervals in place of standard errors.
Walsh, Stephen J.; Tardiff, Mark F.
2007-10-01
Removing background from hyperspectral scenes is a common step in the process of searching for materials of interest. Some approaches to background subtraction use spectral library data and require invertible covariance matrices for each member of the library. This is challenging because the covariance matrix can be calculated but standard methods for estimating the inverse requires that the data set for each library member have many more spectral measurements than spectral channels, which is rarely the case. An alternative approach is called shrinkage estimation. This method is investigated as an approach to providing an invertible covariance matrix estimate in the case where the number of spectral measurements is less than the number of spectral channels. The approach is an analytic method for arriving at a target matrix and the shrinkage parameter that modify the existing covariance matrix for the data to make it invertible. The theory is discussed to develop different estimates. The resulting estimates are computed and inspected on a set of hyperspectral data. This technique shows some promise for arriving at an invertible covariance estimate for small hyperspectral data sets.
Covariance Matrix Estimation for the Cryo-EM Heterogeneity Problem*
Katsevich, E.; Katsevich, A.; Singer, A.
2015-01-01
In cryo-electron microscopy (cryo-EM), a microscope generates a top view of a sample of randomly oriented copies of a molecule. The problem of single particle reconstruction (SPR) from cryo-EM is to use the resulting set of noisy two-dimensional projection images taken at unknown directions to reconstruct the three-dimensional (3D) structure of the molecule. In some situations, the molecule under examination exhibits structural variability, which poses a fundamental challenge in SPR. The heterogeneity problem is the task of mapping the space of conformational states of a molecule. It has been previously suggested that the leading eigenvectors of the covariance matrix of the 3D molecules can be used to solve the heterogeneity problem. Estimating the covariance matrix is challenging, since only projections of the molecules are observed, but not the molecules themselves. In this paper, we formulate a general problem of covariance estimation from noisy projections of samples. This problem has intimate connections with matrix completion problems and high-dimensional principal component analysis. We propose an estimator and prove its consistency. When there are finitely many heterogeneity classes, the spectrum of the estimated covariance matrix reveals the number of classes. The estimator can be found as the solution to a certain linear system. In the cryo-EM case, the linear operator to be inverted, which we term the projection covariance transform, is an important object in covariance estimation for tomographic problems involving structural variation. Inverting it involves applying a filter akin to the ramp filter in tomography. We design a basis in which this linear operator is sparse and thus can be tractably inverted despite its large size. We demonstrate via numerical experiments on synthetic datasets the robustness of our algorithm to high levels of noise. PMID:25699132
On a gauge covariant formulation of string field theories
NASA Astrophysics Data System (ADS)
Ju-Fei, Tang; Chuan-Jie, Zhu
1986-11-01
It is shown that the Neveu-Nicolai-West formulation of the gauge covariant string field theories and that of Banks and Peskin can be obtained by different consistent truncation of the BRST multiplets. A proof is given to show the equivalence of light-cone formulation and the gauge covariant formulation without using the property of trivial cohomology of string differential forms. We would like to thank D.D. Wu and X.J. Zhou for discussion and Yi-Bing Ding for careful reading of the manuscript.
Vector order parameter in general relativity: Covariant equations
Meierovich, Boris E.
2010-07-15
Phase transitions with spontaneous symmetry breaking and vector order parameter are considered in multidimensional theory of general relativity. Covariant equations, describing the gravitational properties of topological defects, are derived. The topological defects are classified in accordance with the symmetry of the covariant derivative of the vector order parameter. The abilities of the derived equations are demonstrated in application to the braneworld concept. New solutions of the Einstein equations with a transverse vector order parameter are presented. In the vicinity of phase transition, the solutions are found analytically.
Neutron Resonance Parameters and Covariance Matrix of 239Pu
Derrien, Herve; Leal, Luiz C; Larson, Nancy M
2008-08-01
In order to obtain the resonance parameters in a single energy range and the corresponding covariance matrix, a reevaluation of 239Pu was performed with the code SAMMY. The most recent experimental data were analyzed or reanalyzed in the energy range thermal to 2.5 keV. The normalization of the fission cross section data was reconsidered by taking into account the most recent measurements of Weston et al. and Wagemans et al. A full resonance parameter covariance matrix was generated. The method used to obtain realistic uncertainties on the average cross section calculated by SAMMY or other processing codes was examined.
Lorentz covariance, higher-spin superspaces and self-duality
Devchand, Chandrashekar; Nuyts, Jean
1998-12-15
Lorentz covariant generalisations of the notions of supersymmetry, superspace and self-duality are discussed. The essential idea is to extend standard constructions by allowing tangent vectors and coordinates which transform according to more general Lorentz representations than solely the spinorial and vectorial ones of standard lore. Such superspaces provide model configuration spaces for theories of arbitrary spin fields. Our framework is an elegant one for handling higher-dimensional theories in a manifestly SO(3,1) cavariant fashion. A further application is the construction of a hierarchy of solvable Lorentz covariant systems generalising four-dimensional self-duality.
Realization of the optimal phase-covariant quantum cloning machine
Sciarrino, Fabio; De Martini, Francesco
2005-12-15
In several quantum information (QI) phenomena of large technological importance the information is carried by the phase of the quantum superposition states, or qubits. The phase-covariant cloning machine (PQCM) addresses precisely the problem of optimally copying these qubits with the largest attainable 'fidelity'. We present a general scheme which realizes the 1{yields}3 phase covariant cloning process by a combination of three different QI processes: the universal cloning, the NOT gate, and the projection over the symmetric subspace of the output qubits. The experimental implementation of a PQCM for polarization encoded qubits, the first ever realized with photons, is reported.
Quasilocal conserved charges in a covariant theory of gravity.
Kim, Wontae; Kulkarni, Shailesh; Yi, Sang-Heon
2013-08-23
In any generally covariant theory of gravity, we show the relationship between the linearized asymptotically conserved current and its nonlinear completion through the identically conserved current. Our formulation for conserved charges is based on the Lagrangian description, and so completely covariant. By using this result, we give a prescription to define quasilocal conserved charges in any higher derivative gravity. As applications of our approach, we demonstrate the angular momentum invariance along the radial direction of black holes and reproduce more efficiently the linearized potential on the asymptotic anti-de Sitter space. PMID:24010423
Derivation of manifestly covariant quantum models for spinning relativistic particles
NASA Astrophysics Data System (ADS)
Marnelius, Robert; Mårtensson, Ulf
1990-05-01
A method to construct manifestly covariant models for relativistic spinning particles is given. The models involve manifestly covariant internal variables leading to discrete state spaces apart from the coordinate and momentum variables. The precise form of the models are extracted from the Bargmann-Wigner conditions on the Pauli-Lubanski operator, together with some consistency conditions. Several simple models are derived and analysed, some of which are new. Also manifestly conformally invariant models for particles with arbitrary spins are derived using a condition of Bracken and Jessup.
Pimentel, Samuel D.; Kelz, Rachel R.; Silber, Jeffrey H.; Rosenbaum, Paul R.
2015-01-01
Every newly trained surgeon performs her first unsupervised operation. How do the health outcomes of her patients compare with the patients of experienced surgeons? Using data from 498 hospitals, we compare 1252 pairs comprised of a new surgeon and an experienced surgeon working at the same hospital. We introduce a new form of matching that matches patients of each new surgeon to patients of an otherwise similar experienced surgeon at the same hospital, perfectly balancing 176 surgical procedures and closely balancing a total of 2.9 million categories of patients; additionally, the individual patient pairs are as close as possible. A new goal for matching is introduced, called “refined covariate balance,” in which a sequence of nested, ever more refined, nominal covariates is balanced as closely as possible, emphasizing the first or coarsest covariate in that sequence. A new algorithm for matching is proposed and the main new results prove that the algorithm finds the closest match in terms of the total within-pair covariate distances among all matches that achieve refined covariate balance. Unlike previous approaches to forcing balance on covariates, the new algorithm creates multiple paths to a match in a network, where paths that introduce imbalances are penalized and hence avoided to the extent possible. The algorithm exploits a sparse network to quickly optimize a match that is about two orders of magnitude larger than is typical in statistical matching problems, thereby permitting much more extensive use of fine and near-fine balance constraints. The match was constructed in a few minutes using a network optimization algorithm implemented in R. An R package called rcbalance implementing the method is available from CRAN. PMID:26273117
NASA Astrophysics Data System (ADS)
Heiker, Andrea; Kutterer, Hansjörg
2010-05-01
The Earth rotation variability is redundantly described by the combination of Earth rotation parameters (polar motion and length of day), geophysical excitation functions and second degree gravity field coefficients. There exist some publications regarding the comparison of the Earth rotation parameters and excitation functions. However, most authors do not make use of the redundancy. In addition, existing covariances between the input parameters are not considered. As shown in previous publications we use the redundancy for the independent mutual validation of the Earth rotation parameters, excitation functions and second degree gravity field coefficients based on an extended Gauss-Markov model and least-squares adjustment. The work regarding the mutual validation is performed within the project P9 "Combined analysis and validation of Earth rotation models and observations" of the research Unit FOR 584 ("Earth rotation and global dynamic processes") which is funded by the German Research Unit (DFG); see also abstract "Combined Analysis and Validation of Earth Rotation Models and Observations". The adjustment model is determined at first by the joint functional relations between the parameters and second by the stochastic model of the input data. A variance-covariance component estimation is included in the adjustment model. The functional model is based on the linearized Euler-Liouville equation. The construction of an appropriate stochastic model is prevented in practice by insufficient knowledge on variances and covariances. However, some numerical results derived from arbitrarily chosen stochastic models indicate that the stochastic model may be crucial for a correct estimation. The missing information is approximated by analyzing the input data. Synthetic variance-covariance matrices are constructed by considering empirical auto- and cross-correlation functions. The influence of neglected covariances is quantified and discussed by comparing the results derived
Covariation between human pelvis shape, stature, and head size alleviates the obstetric dilemma.
Fischer, Barbara; Mitteroecker, Philipp
2015-05-01
Compared with other primates, childbirth is remarkably difficult in humans because the head of a human neonate is large relative to the birth-relevant dimensions of the maternal pelvis. It seems puzzling that females have not evolved wider pelvises despite the high maternal mortality and morbidity risk connected to childbirth. Despite this seeming lack of change in average pelvic morphology, we show that humans have evolved a complex link between pelvis shape, stature, and head circumference that was not recognized before. The identified covariance patterns contribute to ameliorate the "obstetric dilemma." Females with a large head, who are likely to give birth to neonates with a large head, possess birth canals that are shaped to better accommodate large-headed neonates. Short females with an increased risk of cephalopelvic mismatch possess a rounder inlet, which is beneficial for obstetrics. We suggest that these covariances have evolved by the strong correlational selection resulting from childbirth. Although males are not subject to obstetric selection, they also show part of these association patterns, indicating a genetic-developmental origin of integration. PMID:25902498
An Empirical State Error Covariance Matrix Orbit Determination Example
NASA Technical Reports Server (NTRS)
Frisbee, Joseph H., Jr.
2015-01-01
State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. First, consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. Then it follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix of the estimate will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully include all of the errors in the state estimate. The empirical error covariance matrix is determined from a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm. It is a formally correct, empirical state error covariance matrix obtained through use of the average form of the weighted measurement residual variance performance index rather than the usual total weighted residual form. Based on its formulation, this matrix will contain the total uncertainty in the state estimate, regardless as to the source of the uncertainty and whether the source is anticipated or not. It is expected that the empirical error covariance matrix will give a better, statistical representation of the state error in poorly modeled systems or when sensor performance
Meirelles, S L C; Mokry, F B; Espasandín, A C; Dias, M A D; Baena, M M; de A Regitano, L C
2016-01-01
Correlation between genetic parameters and factors such as backfat thickness (BFT), rib eye area (REA), and body weight (BW) were estimated for Canchim beef cattle raised in natural pastures of Brazil. Data from 1648 animals were analyzed using multi-trait (BFT, REA, and BW) animal models by the Bayesian approach. This model included the effects of contemporary group, age, and individual heterozygosity as covariates. In addition, direct additive genetic and random residual effects were also analyzed. Heritability estimated for BFT (0.16), REA (0.50), and BW (0.44) indicated their potential for genetic improvements and response to selection processes. Furthermore, genetic correlations between BW and the remaining traits were high (P > 0.50), suggesting that selection for BW could improve REA and BFT. On the other hand, genetic correlation between BFT and REA was low (P = 0.39 ± 0.17), and included considerable variations, suggesting that these traits can be jointly included as selection criteria without influencing each other. We found that REA and BFT responded to the selection processes, as measured by ultrasound. Therefore, selection for yearling weight results in changes in REA and BFT. PMID:27323151
Genetic grouping strategies in selection efficiency of composite beef cattle ( × ).
Petrini, J; Pertile, S F N; Eler, J P; Ferraz, J B S; Mattos, E C; Figueiredo, L G G; Mourão, G B
2015-02-01
The inclusion of genetic groups in sire evaluation has been widely used to represent genetic differences among animals not accounted for by the absence of parentage data. However, the definition of these groups is still arbitrary, and studies assessing the effects of genetic grouping strategies on the selection efficiency are rare. Therefore, the aim in this study was to compare genetic grouping strategies for animals with unknown parentage in prediction of breeding values (EBV). The total of 179,302 records of weaning weight (WW), 29,825 records of scrotal circumference (SC), and 70,302 records of muscling score (MUSC) from Montana Tropical animals, a Brazilian composite beef cattle population, were used. Genetic grouping strategies involving year of birth, sex of the unknown parent, birth farm, breed composition, and their combinations were evaluated. Estimated breeding values were predicted for each approach simulating a loss of genealogy data. Thereafter, these EBV were compared to those obtained in an analysis involving a real relationship matrix to estimate selection efficiency and correlations between EBV and animal rankings. The analysis model included the fixed effects of contemporary groups and class of the dam age at calving, the covariates of additive and nonadditive genetic effects, and age, and the additive genetic effect of animal as random effects. A second model also included the fixed effects of genetic group. The use of genetic groups resulted in means of selection efficiency and correlation of 70.4 to 97.1% and 0.51 to 0.94 for WW, 85.8 to 98.8% and 0.82 to 0.98 for SC, and 85.1 to 98.6% and 0.74 to 0.97 for MUSC, respectively. High selection efficiencies were observed for year of birth and breed composition strategies. The maximum absolute difference in annual genetic gain estimated through the use of complete genealogy and genetic groups were 0.38 kg for WW, 0.02 cm for SC, and 0.01 for MUSC, with lower differences obtained when year of birth
Nora, J.J.; Fraser, F.C.
1989-01-01
This book presents a discussion of medical genetics for the practitioner treating or counseling patients with genetic disease. It includes a discussion of the relationship of heredity and diseases, the chromosomal basis for heredity, gene frequencies, and genetics of development and maldevelopment. The authors also focus on teratology, somatic cell genetics, genetics and cancer, genetics of behavior.
Compressive sensing beamforming based on covariance for acoustic imaging with noisy measurements.
Zhong, Siyang; Wei, Qingkai; Huang, Xun
2013-11-01
Compressive sensing, a newly emerging method from information technology, is applied to array beamforming and associated acoustic applications. A compressive sensing beamforming method (CSB-II) is developed based on sampling covariance matrix, assuming spatially sparse and incoherent signals, and then examined using both simulations and aeroacoustic measurements. The simulation results clearly show that the proposed CSB-II method is robust to sensing noise. In addition, aeroacoustic tests of a landing gear model demonstrate the good performance in terms of resolution and sidelobe rejection. PMID:24181989
A consistent local linear estimator of the covariate adjusted correlation coefficient
Nguyen, Danh V.; Şentürk, Damla
2009-01-01
Consider the correlation between two random variables (X, Y), both not directly observed. One only observes X̃ = φ1(U)X + φ2(U) and Ỹ = ψ1(U)Y + ψ2(U), where all four functions {φl(·),ψl(·), l = 1, 2} are unknown/unspecified smooth functions of an observable covariate U. We consider consistent estimation of the correlation between the unobserved variables X and Y, adjusted for the above general dual additive and multiplicative effects of U, based on the observed data (X̃, Ỹ, U). PMID:21720454
McGlothlin, Anna; Stamey, James D; Seaman, John W
2008-02-01
We consider a Bayesian analysis for modeling a binary response that is subject to misclassification. Additionally, an explanatory variable is assumed to be unobservable, but measurements are available on its surrogate. A binary regression model is developed to incorporate the measurement error in the covariate as well as the misclassification in the response. Unlike existing methods, no model parameters need be assumed known. Markov chain Monte Carlo methods are utilized to perform the necessary computations. The methods developed are illustrated using atomic bomb survival data. A simulation experiment explores advantages of the approach. PMID:18283683
Variance and Covariance of Actual Relationships between Relatives at One Locus
Garcia-Cortes, Luis Alberto; Legarra, Andres; Chevalet, Claude; Toro, Miguel Angel
2013-01-01
The relationship between pairs of individuals is an important topic in many areas of population and quantitative genetics. It is usually measured as the proportion of thegenome identical by descent shared by the pair and it can be inferred from pedigree information. But there is a variance in actual relationships as a consequence of Mendelian sampling, whose general formula has not been developed. The goal of this work is to develop this general formula for the one-locus situation,. We provide simple expressions for the variances and covariances of all actual relationships in an arbitrary complex pedigree. The proposed method relies on the use of the nine identity coefficients and the generalized relationship coefficients; formulas have been checked by computer simulation. Finally two examples for a short pedigree of dogs and a long pedigree of sheep are given. PMID:23451134
Covariance of lichen and vascular plant floras
Bennett, J.P.; Wetmore, C.M.
1999-01-01
The geographic relationships among taxonomic groups are important to study to determine patterns of biodiversity and whether or not associations occur between large groups, e.g., birds and vascular plants. This study was undertaken to determine relationships between higher plants and lower plants, specifically vascular plant and lichen floras in nine national parks of the Great Lakes region. No significant relationship was found between vascular plant floras and lichen floras in this area, which spans 1200 km longitudinally, or between an additional 19 areas from North America that were less than 1000 km(2) in area. For areas larger than 1000 km(2), however, a significant positive relationship existed for 33 areas that span one to approximately 150 million km(2). The ratio of numbers of vascular plants to lichens appeared to average just over 6 across the 33 areas. In the Great Lakes parks, between 28-30% of either the vascular plant or lichen species were singletons (occurring in only one park), but the parks that contained the most singletons were not congruent: Isle Royale had the most singleton lichens, while Indiana Dunes had the most vascular plant singletons. Fewer lichen species (2%) than vascular plants (4%) occurred in all nine parks. Latitude appeared to explain some of the variation between the two groups: vascular plants decreased with increasing latitude, while lichens increased.
General covariance constraints on cosmological correlators
Armendariz-Picon, Cristian; Neelakanta, Jayanth T.; Penco, Riccardo E-mail: jtneelak@syr.edu
2015-01-01
We study the extent to which diffeomorphism invariance restricts the properties of the perturbations in single scalar field cosmological models. We derive a set of identities that constrain the connected correlators of the cosmological perturbations, as well as the one-particle-irreducible vertices of the theory in any gauge. These identities are the analogues of Slavnov-Taylor identities in gauge theories, and follow essentially from diffeomorphism invariance alone. Yet because quantization requires diffeomorphism invariance to be broken, they not only reflect invariance under diffeomorphisms, but also how the latter has been broken by gauge fixing terms. In order not to lose the symmetry altogether, we cannot simply set some fields to zero, as is usually done in cosmological perturbation theory, but need to decouple them smoothly and make sure that they do not contribute to cosmological correlators in the decoupling limit. We use these identities to derive a set of consistency relations between bispectra and power spectra of cosmological perturbations in different gauges. Without additional assumptions, these consistency relations just seem to reflect the redundancy implied by diffeomorphisms. But when combined with analyticity, in a formulation of the theory in which auxiliary fields have been integrated out, we recover novel and previously derived relations that follow from invariance under both time and spatial diffeomorphisms.
On variance estimate for covariate adjustment by propensity score analysis.
Zou, Baiming; Zou, Fei; Shuster, Jonathan J; Tighe, Patrick J; Koch, Gary G; Zhou, Haibo
2016-09-10
Propensity score (PS) methods have been used extensively to adjust for confounding factors in the statistical analysis of observational data in comparative effectiveness research. There are four major PS-based adjustment approaches: PS matching, PS stratification, covariate adjustment by PS, and PS-based inverse probability weighting. Though covariate adjustment by PS is one of the most frequently used PS-based methods in clinical research, the conventional variance estimation of the treatment effects estimate under covariate adjustment by PS is biased. As Stampf et al. have shown, this bias in variance estimation is likely to lead to invalid statistical inference and could result in erroneous public health conclusions (e.g., food and drug safety and adverse events surveillance). To address this issue, we propose a two-stage analytic procedure to develop a valid variance estimator for the covariate adjustment by PS analysis strategy. We also carry out a simple empirical bootstrap resampling scheme. Both proposed procedures are implemented in an R function for public use. Extensive simulation results demonstrate the bias in the conventional variance estimator and show that both proposed variance estimators offer valid estimates for the true variance, and they are robust to complex confounding structures. The proposed methods are illustrated for a post-surgery pain study. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26999553
Covariation of Color and Luminance Facilitate Object Individuation in Infancy
ERIC Educational Resources Information Center
Woods, Rebecca J.; Wilcox, Teresa
2010-01-01
The ability to individuate objects is one of our most fundamental cognitive capacities. Recent research has revealed that when objects vary in color or luminance alone, infants fail to individuate those objects until 11.5 months. However, color and luminance frequently covary in the natural environment, thus providing a more salient and reliable…
Eddy covariance based methane flux in Sundarbans mangroves, India
NASA Astrophysics Data System (ADS)
Jha, Chandra Shekhar; Rodda, Suraj Reddy; Thumaty, Kiran Chand; Raha, A. K.; Dadhwal, V. K.
2014-06-01
We report the initial results of the methane flux measured using eddy covariance method during summer months from the world's largest mangrove ecosystem, Sundarbans of India. Mangrove ecosystems are known sources for methane (CH4) having very high global warming potential. In order to quantify the methane flux in mangroves, an eddy covariance flux tower was recently erected in the largest unpolluted and undisturbed mangrove ecosystem in Sundarbans (India). The tower is equipped with eddy covariance flux tower instruments to continuously measure methane fluxes besides the mass and energy fluxes. This paper presents the preliminary results of methane flux variations during summer months (i.e., April and May 2012) in Sundarbans mangrove ecosystem. The mean concentrations of CH4 emission over the study period was 1682 ± 956 ppb. The measured CH4 fluxes computed from eddy covariance technique showed that the study area acts as a net source for CH4 with daily mean flux of 150.22 ± 248.87 mg m-2 day-1. The methane emission as well as its flux showed very high variability diurnally. Though the environmental conditions controlling methane emission is not yet fully understood, an attempt has been made in the present study to analyse the relationships of methane efflux with tidal activity. This present study is part of Indian Space Research Organisation-Geosphere Biosphere Program (ISRO-GBP) initiative under `National Carbon Project'.
A Review of Nonparametric Alternatives to Analysis of Covariance.
ERIC Educational Resources Information Center
Olejnik, Stephen F.; Algina, James
1985-01-01
Five distribution-free alternatives to parametric analysis of covariance are presented and demonstrated: Quade's distribution-free test, Puri and Sen's solution, McSweeney and Porter's rank transformation, Burnett and Barr's rank difference scores, and Shirley's general linear model solution. The results of simulation studies regarding Type I…
A Review of Nonparametric Alternatives to Analysis of Covariance.
ERIC Educational Resources Information Center
Olejnik, Stephen F.; Algina, James
Five distribution-free alternatives to parametric analysis of covariance (ANCOVA) are presented and demonstrated using a specific data example. The procedures considered are those suggested by Quade (1967); Puri and Sen (1969); McSweeney and Porter (1971); Burnett and Barr (1978); and Shirley (1981). The results of simulation studies investigating…
Altered Cerebral Blood Flow Covariance Network in Schizophrenia
Liu, Feng; Zhuo, Chuanjun; Yu, Chunshui
2016-01-01
Many studies have shown abnormal cerebral blood flow (CBF) in schizophrenia; however, it remains unclear how topological properties of CBF network are altered in this disorder. Here, arterial spin labeling (ASL) MRI was employed to measure resting-state CBF in 96 schizophrenia patients and 91 healthy controls. CBF covariance network of each group was constructed by calculating across-subject CBF covariance between 90 brain regions. Graph theory was used to compare intergroup differences in global and nodal topological measures of the network. Both schizophrenia patients and healthy controls had small-world topology in CBF covariance networks, implying an optimal balance between functional segregation and integration. Compared with healthy controls, schizophrenia patients showed reduced small-worldness, normalized clustering coefficient and local efficiency of the network, suggesting a shift toward randomized network topology in schizophrenia. Furthermore, schizophrenia patients exhibited altered nodal centrality in the perceptual-, affective-, language-, and spatial-related regions, indicating functional disturbance of these systems in schizophrenia. This study demonstrated for the first time that schizophrenia patients have disrupted topological properties in CBF covariance network, which provides a new perspective (efficiency of blood flow distribution between brain regions) for understanding neural mechanisms of schizophrenia. PMID:27445677
Model Comparison of Nonlinear Structural Equation Models with Fixed Covariates.
ERIC Educational Resources Information Center
Lee, Sik-Yum; Song, Xin-Yuan
2003-01-01
Proposed a new nonlinear structural equation model with fixed covariates to deal with some complicated substantive theory and developed a Bayesian path sampling procedure for model comparison. Illustrated the approach with an illustrative example using data from an international study. (SLD)
Experimental Analysis of Response Covariation among Compliant and Inappropriate Behaviors.
ERIC Educational Resources Information Center
Parrish, John M.; And Others
1986-01-01
The study investigated the relationship between topographically different child behaviors (compliance and inappropriate activities) in four mentally retarded subjects (aged 3-5) by using a methodology that tests for response covariation. Regardless of the intervention used, the behavior targeted, or the direction manipulated, the nontargeted…
A new eddy-covariance method using empirical mode decomposition
Technology Transfer Automated Retrieval System (TEKTRAN)
We introduce a new eddy-covariance method that uses a spectral decomposition algorithm called empirical mode decomposition. The technique is able to calculate contributions to near-surface fluxes from different periodic components. Unlike traditional Fourier methods, this method allows for non-ortho...
Covariance matrices for use in criticality safety predictability studies
Derrien, H.; Larson, N.M.; Leal, L.C.
1997-09-01
Criticality predictability applications require as input the best available information on fissile and other nuclides. In recent years important work has been performed in the analysis of neutron transmission and cross-section data for fissile nuclei in the resonance region by using the computer code SAMMY. The code uses Bayes method (a form of generalized least squares) for sequential analyses of several sets of experimental data. Values for Reich-Moore resonance parameters, their covariances, and the derivatives with respect to the adjusted parameters (data sensitivities) are obtained. In general, the parameter file contains several thousand values and the dimension of the covariance matrices is correspondingly large. These matrices are not reported in the current evaluated data files due to their large dimensions and to the inadequacy of the file formats. The present work has two goals: the first is to calculate the covariances of group-averaged cross sections from the covariance files generated by SAMMY, because these can be more readily utilized in criticality predictability calculations. The second goal is to propose a more practical interface between SAMMY and the evaluated files. Examples are given for {sup 235}U in the popular 199- and 238-group structures, using the latest ORNL evaluation of the {sup 235}U resonance parameters.
Altered Cerebral Blood Flow Covariance Network in Schizophrenia.
Liu, Feng; Zhuo, Chuanjun; Yu, Chunshui
2016-01-01
Many studies have shown abnormal cerebral blood flow (CBF) in schizophrenia; however, it remains unclear how topological properties of CBF network are altered in this disorder. Here, arterial spin labeling (ASL) MRI was employed to measure resting-state CBF in 96 schizophrenia patients and 91 healthy controls. CBF covariance network of each group was constructed by calculating across-subject CBF covariance between 90 brain regions. Graph theory was used to compare intergroup differences in global and nodal topological measures of the network. Both schizophrenia patients and healthy controls had small-world topology in CBF covariance networks, implying an optimal balance between functional segregation and integration. Compared with healthy controls, schizophrenia patients showed reduced small-worldness, normalized clustering coefficient and local efficiency of the network, suggesting a shift toward randomized network topology in schizophrenia. Furthermore, schizophrenia patients exhibited altered nodal centrality in the perceptual-, affective-, language-, and spatial-related regions, indicating functional disturbance of these systems in schizophrenia. This study demonstrated for the first time that schizophrenia patients have disrupted topological properties in CBF covariance network, which provides a new perspective (efficiency of blood flow distribution between brain regions) for understanding neural mechanisms of schizophrenia. PMID:27445677
Latent Variable Models of Genotype-Environment Covariance.
ERIC Educational Resources Information Center
Hershberger, Scott L.
2003-01-01
Results of a study involving 136 pairs of identical twins reared together, 175 pairs of fraternal twins reared together, 83 pairs of identical twins reared apart, and 182 pairs of fraternal twins reared apart suggest that genotype- environment covariance is important for the work environment and should be included as a parameter in behavior…
Eddy Covariance Measurements of the Sea-Spray Aerosol Flu
NASA Astrophysics Data System (ADS)
Brooks, I. M.; Norris, S. J.; Yelland, M. J.; Pascal, R. W.; Prytherch, J.
2015-12-01
Historically, almost all estimates of the sea-spray aerosol source flux have been inferred through various indirect methods. Direct estimates via eddy covariance have been attempted by only a handful of studies, most of which measured only the total number flux, or achieved rather coarse size segregation. Applying eddy covariance to the measurement of sea-spray fluxes is challenging: most instrumentation must be located in a laboratory space requiring long sample lines to an inlet collocated with a sonic anemometer; however, larger particles are easily lost to the walls of the sample line. Marine particle concentrations are generally low, requiring a high sample volume to achieve adequate statistics. The highly hygroscopic nature of sea salt means particles change size rapidly with fluctuations in relative humidity; this introduces an apparent bias in flux measurements if particles are sized at ambient humidity. The Compact Lightweight Aerosol Spectrometer Probe (CLASP) was developed specifically to make high rate measurements of aerosol size distributions for use in eddy covariance measurements, and the instrument and data processing and analysis techniques have been refined over the course of several projects. Here we will review some of the issues and limitations related to making eddy covariance measurements of the sea spray source flux over the open ocean, summarise some key results from the last decade, and present new results from a 3-year long ship-based measurement campaign as part of the WAGES project. Finally we will consider requirements for future progress.
Conditional Covariance-based Representation of Multidimensional Test Structure.
ERIC Educational Resources Information Center
Bolt, Daniel M.
2001-01-01
Presents a new nonparametric method for constructing a spatial representation of multidimensional test structure, the Conditional Covariance-based SCALing (CCSCAL) method. Describes an index to measure the accuracy of the representation. Uses simulation and real-life data analyses to show that the method provides a suitable approximation to…
Triangular covariance factorizations for. Ph.D. Thesis. - Calif. Univ.
NASA Technical Reports Server (NTRS)
Thornton, C. L.
1976-01-01
An improved computational form of the discrete Kalman filter is derived using an upper triangular factorization of the error covariance matrix. The covariance P is factored such that P = UDUT where U is unit upper triangular and D is diagonal. Recursions are developed for propagating the U-D covariance factors together with the corresponding state estimate. The resulting algorithm, referred to as the U-D filter, combines the superior numerical precision of square root filtering techniques with an efficiency comparable to that of Kalman's original formula. Moreover, this method is easily implemented and involves no more computer storage than the Kalman algorithm. These characteristics make the U-D method an attractive realtime filtering technique. A new covariance error analysis technique is obtained from an extension of the U-D filter equations. This evaluation method is flexible and efficient and may provide significantly improved numerical results. Cost comparisons show that for a large class of problems the U-D evaluation algorithm is noticeably less expensive than conventional error analysis methods.
Manufacturing time operators: Covariance, selection criteria, and examples
Hegerfeldt, G. C.; Muga, J. G.; Munoz, J.
2010-07-15
We provide the most general forms of covariant and normalized time operators and their probability densities, with applications to quantum clocks, the time of arrival, and Lyapunov quantum operators. Examples are discussed of the profusion of possible operators and their physical meaning. Criteria to define unique, optimal operators for specific cases are given.
Efficient retrieval of landscape Hessian: forced optimal covariance adaptive learning.
Shir, Ofer M; Roslund, Jonathan; Whitley, Darrell; Rabitz, Herschel
2014-06-01
Knowledge of the Hessian matrix at the landscape optimum of a controlled physical observable offers valuable information about the system robustness to control noise. The Hessian can also assist in physical landscape characterization, which is of particular interest in quantum system control experiments. The recently developed landscape theoretical analysis motivated the compilation of an automated method to learn the Hessian matrix about the global optimum without derivative measurements from noisy data. The current study introduces the forced optimal covariance adaptive learning (FOCAL) technique for this purpose. FOCAL relies on the covariance matrix adaptation evolution strategy (CMA-ES) that exploits covariance information amongst the control variables by means of principal component analysis. The FOCAL technique is designed to operate with experimental optimization, generally involving continuous high-dimensional search landscapes (≳30) with large Hessian condition numbers (≳10^{4}). This paper introduces the theoretical foundations of the inverse relationship between the covariance learned by the evolution strategy and the actual Hessian matrix of the landscape. FOCAL is presented and demonstrated to retrieve the Hessian matrix with high fidelity on both model landscapes and quantum control experiments, which are observed to possess nonseparable, nonquadratic search landscapes. The recovered Hessian forms were corroborated by physical knowledge of the systems. The implications of FOCAL extend beyond the investigated studies to potentially cover other physically motivated multivariate landscapes. PMID:25019911
[Covariance structure analysis of pharmacists' attitudes toward medication history].
Sato, Hirotaka; Shimamori, Yoshimitu
2011-01-01
Keeping track of patients' medication histories is an important component of pharmacy practice. In this study, we conducted a questionnaire survey on medication histories among pharmacists and performed covariance structure analysis to investigate pharmacists' attitudes toward medication histories. The survey was conducted among pharmacists who work at pharmacies. With regard to the questions on medication histories, factor analysis and covariance structure analysis were performed to create a path diagram. The response rate to the questionnaire was 97.0%. The factor analysis revealed six factors, including: "patient assessment", "learning attitude", "practicing the recording of medication histories", "conscious effort to improve medication histories", "uniformity in medication histories" and "issues regarding medication histories". Meanwhile, covariance structure analysis revealed that the five-factor model excluding "issues regarding medication histories" was the best-fitted model. According to this model, it was clear that the pharmacists were extremely conscious about introducing improvements to the content of medication histories. In this study, covariance structure analysis enabled the effective analysis of the attitudes of pharmacists toward medication histories. We believe that creating and conducting a training program to clarify and resolve issues related to medication histories and then reviewing the outcome of such a training program will lead to quality improvement and standardization of the future management of medication histories. PMID:21532278
Effect on Prediction when Modeling Covariates in Bayesian Nonparametric Models.
Cruz-Marcelo, Alejandro; Rosner, Gary L; Müller, Peter; Stewart, Clinton F
2013-04-01
In biomedical research, it is often of interest to characterize biologic processes giving rise to observations and to make predictions of future observations. Bayesian nonparametric methods provide a means for carrying out Bayesian inference making as few assumptions about restrictive parametric models as possible. There are several proposals in the literature for extending Bayesian nonparametric models to include dependence on covariates. Limited attention, however, has been directed to the following two aspects. In this article, we examine the effect on fitting and predictive performance of incorporating covariates in a class of Bayesian nonparametric models by one of two primary ways: either in the weights or in the locations of a discrete random probability measure. We show that different strategies for incorporating continuous covariates in Bayesian nonparametric models can result in big differences when used for prediction, even though they lead to otherwise similar posterior inferences. When one needs the predictive density, as in optimal design, and this density is a mixture, it is better to make the weights depend on the covariates. We demonstrate these points via a simulated data example and in an application in which one wants to determine the optimal dose of an anticancer drug used in pediatric oncology. PMID:23687472
Phenotypic Covariation and Morphological Diversification in the Ruminant Skull.
Haber, Annat
2016-05-01
Differences among clades in their diversification patterns result from a combination of extrinsic and intrinsic factors. In this study, I examined the role of intrinsic factors in the morphological diversification of ruminants, in general, and in the differences between bovids and cervids, in particular. Using skull morphology, which embodies many of the adaptations that distinguish bovids and cervids, I examined 132 of the 200 extant ruminant species. As a proxy for intrinsic constraints, I quantified different aspects of the phenotypic covariation structure within species and compared them with the among-species divergence patterns, using phylogenetic comparative methods. My results show that for most species, divergence is well aligned with their phenotypic covariance matrix and that those that are better aligned have diverged further away from their ancestor. Bovids have dispersed into a wider range of directions in morphospace than cervids, and their overall disparity is higher. This difference is best explained by the lower eccentricity of bovids' within-species covariance matrices. These results are consistent with the role of intrinsic constraints in determining amount, range, and direction of dispersion and demonstrate that intrinsic constraints can influence macroevolutionary patterns even as the covariance structure evolves. PMID:27104991
Students' Notions regarding "Covariance" of a Physical Theory
ERIC Educational Resources Information Center
Bandyopadhyay, Atanu; Kumar, Arvind
2010-01-01
A physical theory is said to be covariant with respect to a certain class of transformations when its basic equations retain their "form" under those transformations. It is one of the basic notions encountered in physics, particularly in the domain of relativity. In this paper we study in some detail how students deal with this notion in different…
Detection of fungal damaged popcorn using image property covariance features
Technology Transfer Automated Retrieval System (TEKTRAN)
Covariance-matrix-based features were applied to the detection of popcorn infected by a fungus that cause a symptom called “blue-eye.” This infection of popcorn kernels causes economic losses because of their poor appearance and the frequently disagreeable flavor of the popped kernels. Images of ker...
RNA search with decision trees and partial covariance models.
Smith, Jennifer A
2009-01-01
The use of partial covariance models to search for RNA family members in genomic sequence databases is explored. The partial models are formed from contiguous subranges of the overall RNA family multiple alignment columns. A binary decision-tree framework is presented for choosing the order to apply the partial models and the score thresholds on which to make the decisions. The decision trees are chosen to minimize computation time subject to the constraint that all of the training sequences are passed to the full covariance model for final evaluation. Computational intelligence methods are suggested to select the decision tree since the tree can be quite complex and there is no obvious method to build the tree in these cases. Experimental results from seven RNA families shows execution times of 0.066-0.268 relative to using the full covariance model alone. Tests on the full sets of known sequences for each family show that at least 95 percent of these sequences are found for two families and 100 percent for five others. Since the full covariance model is run on all sequences accepted by the partial model decision tree, the false alarm rate is at least as low as that of the full model alone. PMID:19644178
Covariance Structure Models for Gene Expression Microarray Data
ERIC Educational Resources Information Center
Xie, Jun; Bentler, Peter M.
2003-01-01
Covariance structure models are applied to gene expression data using a factor model, a path model, and their combination. The factor model is based on a few factors that capture most of the expression information. A common factor of a group of genes may represent a common protein factor for the transcript of the co-expressed genes, and hence, it…
Prediction: Design of experiments based on approximating covariance kernels
Fedorov, V.
1998-11-01
Using Mercer`s expansion to approximate the covariance kernel of an observed random function the authors transform the prediction problem to the regression problem with random parameters. The latter one is considered in the framework of convex design theory. First they formulate results in terms of the regression model with random parameters, then present the same results in terms of the original problem.
A covariant approach to the gravitational refractive index
NASA Astrophysics Data System (ADS)
Simaciu, I.; Ionescu-Pallas, N.
A covariant formulation of the Maxwell's field equations in a gravitational field, based on the bimetric interpretation of general relativity Theory, is given. The purpose of the work is in adequate definition of the gravitational refractive index in agreement with both wave equations propagation and a relationship between refractive index and the Minkovskian tensor of gravitational permitivity.
Gauge covariant fermion propagator in quenched, chirally symmetric quantum electrodynamics
Roberts, C.D.; Dong, Z.; Munczek, H.J.
1995-08-01
The chirally symmetric solution of the massless, quenched, Dyson-Schwinger equation (DSE) for the fermion propagator in three- and four-dimensional quantum electrodynamics was obtained. The DSEs are a valuable nonperturbative tool for studying field theories. In recent years a good deal of progress was made in addressing the limitations of the DSE approach in the study of Abelian gauge theories. Key to this progress is an understanding of the role of the dressed fermion/gauge-boson vertex in ensuring gauge covariance and multiplicative renormalizability of the solution of the fermion DSE. The solutions we obtain are manifestly gauge covariant and a general gauge covariance constraint on the fermion/gauge-boson vertex is presented, which motivates a vertex Ansatz that, for the first time, both satisfies the Ward identity when the fermion self-mass is zero and ensures gauge covariance of the fermion propagator. This research facilitates gauge-invariant, nonperturbative studies of continuum quantum electrodynamics and has already been used by others in studies of the chiral phase transition.
Alternative Test Criteria in Covariance Structure Analysis: A Unified Approach.
ERIC Educational Resources Information Center
Satorra, Albert
1989-01-01
Within covariance structural analysis, a unified approach to asymptotic theory of alternative test criteria for testing parametric restrictions is provided. More general statistics for addressing the case where the discrepancy function is not asymptotically optimal, and issues concerning power analysis and the asymptotic theory of testing-related…
FLUXPART: An FOSS solution for Eddy covariance flux partitioning
Technology Transfer Automated Retrieval System (TEKTRAN)
We report on efforts to develop a FOSS solution for a particular geoscience application. Eddy covariance (EC) instruments are routinely used to measure field-scale evapotranspiration and CO2 fluxes. For many applications, it is desirable to partition the measured evapotranspiration flux into its c...
Determining the oxygen isotope composition of evapotranspiration with eddy covariance
Technology Transfer Automated Retrieval System (TEKTRAN)
The oxygen isotope componsition of evapotranspiration (dF) represents an important tracer in the study of biosphere-atmosphere interactions, hydrology, paleoclimate, and carbon cycling. Here we demonstrate direct measurement of dF based on eddy covariance (EC) and tunable diode laser (EC-TDL) techni...
The QCD evolution of TMD in the covariant approach
NASA Astrophysics Data System (ADS)
Efremov, A. V.; Teryaev, O. V.; Zavada, P.
2016-02-01
The procedure for calculation of the QCD evolution of transverse momentum dependent distributions within the covariant approach is suggested. The standard collinear QCD evolution together with the requirements of relativistic invariance and rotational symmetry of the nucleon in its rest frame represent the basic ingredients of our approach. The obtained results are compared with the predictions of some other approaches.
Some asymptotic properties of kriging when the covariance function is misspecified
Stein, M.L.; Handcock, M.S.
1989-02-01
The impact of using an incorrect covariance function of kriging predictors is investigated. Results of Stein (1988) show that the impact on the kriging predictor from not using the correct covariance function is asymptotically negligible as the number of observations increases if the covariance function used is compatible with the actual covariance function on the region of interest R. The definition and some properties of compatibility of covariance functions are given. The compatibility of generalized covariances also is defined. Compatibility supports the intuitively sensible concept that usually only the behavior near the origin of the covariance function is critical for purposes of kriging. However, the commonly used spherical covariance function is an exception: observations at a distance near the range of a spherical covariance function can have a nonnegligible effect on kriging predictors for three-dimensional processes. Finally, a comparison is made with the perturbation approach of Diamond and Armstrong (1984) and some observations of Warnes (1986) are clarified.
Wass, Christopher; Denman-Brice, Alexander; Rios, Chris; Light, Kenneth R; Kolata, Stefan; Smith, Andrew M; Matzel, Louis D
2012-04-01
Contemporary descriptions of human intelligence hold that this trait influences a broad range of cognitive abilities, including learning, attention, and reasoning. Like humans, individual genetically heterogeneous mice express a "general" cognitive trait that influences performance across a diverse array of learning and attentional tasks, and it has been suggested that this trait is qualitatively and structurally analogous to general intelligence in humans. However, the hallmark of human intelligence is the ability to use various forms of "reasoning" to support solutions to novel problems. Here, we find that genetically heterogeneous mice are capable of solving problems that are nominally indicative of inductive and deductive forms of reasoning, and that individuals' capacity for reasoning covaries with more general learning abilities. Mice were characterized for their general learning ability as determined by their aggregate performance (derived from principal component analysis) across a battery of five diverse learning tasks. These animals were then assessed on prototypic tests indicative of deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping") and inductive reasoning (execution of an efficient search strategy in a binary decision tree). The animals exhibited systematic abilities on each of these nominal reasoning tasks that were predicted by their aggregate performance on the battery of learning tasks. These results suggest that the coregulation of reasoning and general learning performance in genetically heterogeneous mice form a core cognitive trait that is analogous to human intelligence. PMID:22428547
Gibson, Amanda K; Jokela, Jukka; Lively, Curtis M
2016-07-01
The prevalence of infection varies dramatically on a fine spatial scale. Many evolutionary hypotheses are founded on the assumption that this variation is due to host genetics, such that sites with a high frequency of alleles conferring susceptibility are associated with higher infection prevalence. This assumption is largely untested and may be compromised at finer spatial scales where gene flow between sites is high. We put this assumption to the test in a natural snail-trematode interaction in which host susceptibility is known to have a strong genetic basis. A decade of field sampling revealed substantial spatial variation in infection prevalence between 13 sites around a small lake. Laboratory assays replicated over 3 years demonstrate striking variation in host susceptibility among sites in spite of high levels of gene flow between sites. We find that mean susceptibility can explain more than one-third of the observed variation in mean infection prevalence among sites. We estimate that variation in susceptibility and exposure together can explain the majority of variation in prevalence. Overall, our findings in this natural host-parasite system argue that spatial variation in infection prevalence covaries strongly with variation in the distribution of genetically based susceptibility, even at a fine spatial scale. PMID:27322117
Bispectrum covariance in the flat-sky limit
NASA Astrophysics Data System (ADS)
Joachimi, B.; Shi, X.; Schneider, P.
2009-12-01
Aims. To probe cosmological fields beyond the Gaussian level, three-point statistics can be used, all of which are related to the bispectrum. Hence, measurements of CMB anisotropies, galaxy clustering, and weak gravitational lensing alike have to rely upon an accurate theoretical background concerning the bispectrum and its noise properties. If only small portions of the sky are considered, it is often desirable to perform the analysis in the flat-sky limit. We aim at a formal, detailed derivation of the bispectrum covariance in the flat-sky approximation, focusing on a pure two-dimensional Fourier-plane approach. Methods: We define an unbiased estimator of the bispectrum, which takes the average over the overlap of annuli in Fourier space, and compute its full covariance. The outcome of our formalism is compared to the flat-sky spherical harmonic approximation in terms of the covariance, the behavior under parity transformations, and the information content. We introduce a geometrical interpretation of the averaging process in the estimator, thus providing an intuitive understanding. Results: Contrary to foregoing work, we find a difference by a factor of two between the covariances of the Fourier-plane and the spherical harmonic approach. We argue that this discrepancy can be explained by the differing behavior with respect to parity. However, in an exemplary analysis it is demonstrated that the Fisher information of both formalisms agrees to high accuracy. Via the geometrical interpretation we are able to link the normalization in the bispectrum estimator to the area enclosed by the triangle configuration at consideration as well as to the Wigner symbol, which leads to convenient approximation formulae for the covariances of both approaches.
Assessing spatial covariance among time series of abundance.
Jorgensen, Jeffrey C; Ward, Eric J; Scheuerell, Mark D; Zabel, Richard W
2016-04-01
For species of conservation concern, an essential part of the recovery planning process is identifying discrete population units and their location with respect to one another. A common feature among geographically proximate populations is that the number of organisms tends to covary through time as a consequence of similar responses to exogenous influences. In turn, high covariation among populations can threaten the persistence of the larger metapopulation. Historically, explorations of the covariance in population size of species with many (>10) time series have been computationally difficult. Here, we illustrate how dynamic factor analysis (DFA) can be used to characterize diversity among time series of population abundances and the degree to which all populations can be represented by a few common signals. Our application focuses on anadromous Chinook salmon (Oncorhynchus tshawytscha), a species listed under the US Endangered Species Act, that is impacted by a variety of natural and anthropogenic factors. Specifically, we fit DFA models to 24 time series of population abundance and used model selection to identify the minimum number of latent variables that explained the most temporal variation after accounting for the effects of environmental covariates. We found support for grouping the time series according to 5 common latent variables. The top model included two covariates: the Pacific Decadal Oscillation in spring and summer. The assignment of populations to the latent variables matched the currently established population structure at a broad spatial scale. At a finer scale, there was more population grouping complexity. Some relatively distant populations were grouped together, and some relatively close populations - considered to be more aligned with each other - were more associated with populations further away. These coarse- and fine-grained examinations of spatial structure are important because they reveal different structural patterns not evident
Hirarchical Bayesian Spatio-Temporal Interpolation including Covariates
NASA Astrophysics Data System (ADS)
Hussain, Ijaz; Mohsin, Muhammad; Spoeck, Gunter; Pilz, Juergen
2010-05-01
The space-time interpolation of precipitation has significant contribution to river control,reservoir operations, forestry interest and flash flood watches etc. The changes in environmental covariates and spatial covariates make space-time estimation of precipitation a challenging task. In our earlier paper [1], we used transformed hirarchical Bayesian sapce-time interpolation method for predicting the amount of precipiation. In present paper, we modified the [2] method to include covarites which varaies with respect to space-time. The proposed method is applied to estimating space-time monthly precipitation in the monsoon periods during 1974 - 2000. The 27-years monthly average data of precipitation, temperature, humidity and wind speed are obtained from 51 monitoring stations in Pakistan. The average monthly precipitation is used response variable and temperature, humidity and wind speed are used as time varying covariates. Moreovere the spatial covarites elevation, latitude and longitude of same monitoring stations are also included. The cross-validation method is used to compare the results of transformed hierarchical Bayesian spatio-temporal interpolation with and without including environmental and spatial covariates. The software of [3] is modified to incorprate enviornmental covariates and spatil covarites. It is observed that the transformed hierarchical Bayesian method including covarites provides more accuracy than the transformed hierarchical Bayesian method without including covarites. Moreover, the five potential monitoring cites are selected based on maximum entropy sampaling design approach. References [1] I.Hussain, J.Pilz,G. Spoeck and H.L.Yu. Spatio-Temporal Interpolation of Precipitation during Monsoon Periods in Pakistan. submitted in Advances in water Resources,2009. [2] N.D. Le, W. Sun, and J.V. Zidek, Bayesian multivariate spatial interpolation with data missing by design. Journal of the Royal Statistical Society. Series B (Methodological
Quantitative genetics of migration-related traits in rainbow and steelhead trout.
Hecht, Benjamin C; Hard, Jeffrey J; Thrower, Frank P; Nichols, Krista M
2015-05-01
Rainbow trout (Oncorhynchus mykiss) exhibit remarkable life history diversity throughout their native range, and among the most evident is variation in migratory propensity. Although some populations and ecotypes will remain resident in freshwater habitats throughout their life history, others have the ability to undertake tremendous marine migrations. Those that migrate undergo a suite of behavioral, morphological, and physiological adaptations in a process called smoltification. We describe a quantitative genetic analysis of 22 growth, size, and morphological traits in addition to overall life history classification (resident or migrant) over the temporal process of smoltification in a large multi-generation experimental pedigree (n = 16,139) of migratory and resident rainbow trout derived from a wild population, which naturally segregates for migratory propensity. We identify significant additive genetic variance and covariance among the suite of traits that make up a component of the migratory syndrome in this species. Additionally, we identify high heritability estimates for the life history classifications and observe a strong negative genetic correlation between the migratory and resident life history trajectories. Given the large heritability estimates of all of the traits that segregate between migratory and resident rainbow trout, we conclude that these traits can respond to selection. However, given the high degree of genetic correlation between these traits, they do not evolve in isolation, but rather as a suite of coordinated characters in a predictable manner. PMID:25784164
Quantitative Genetics of Migration-Related Traits in Rainbow and Steelhead Trout
Hecht, Benjamin C.; Hard, Jeffrey J.; Thrower, Frank P.
2015-01-01
Rainbow trout (Oncorhynchus mykiss) exhibit remarkable life history diversity throughout their native range, and among the most evident is variation in migratory propensity. Although some populations and ecotypes will remain resident in freshwater habitats throughout their life history, others have the ability to undertake tremendous marine migrations. Those that migrate undergo a suite of behavioral, morphological, and physiological adaptations in a process called smoltification. We describe a quantitative genetic analysis of 22 growth, size, and morphological traits in addition to overall life history classification (resident or migrant) over the temporal process of smoltification in a large multi-generation experimental pedigree (n = 16,139) of migratory and resident rainbow trout derived from a wild population, which naturally segregates for migratory propensity. We identify significant additive genetic variance and covariance among the suite of traits that make up a component of the migratory syndrome in this species. Additionally, we identify high heritability estimates for the life history classifications and observe a strong negative genetic correlation between the migratory and resident life history trajectories. Given the large heritability estimates of all of the traits that segregate between migratory and resident rainbow trout, we conclude that these traits can respond to selection. However, given the high degree of genetic correlation between these traits, they do not evolve in isolation, but rather as a suite of coordinated characters in a predictable manner. PMID:25784164
Leger, Kasey J; Cushing-Haugen, Kara; Hansen, John A; Fan, Wenhong; Leisenring, Wendy M; Martin, Paul J; Zhao, Lue Ping; Chow, Eric J
2016-06-01
Cardiomyopathy has been recognized as a complication after hematopoietic cell transplantation (HCT). Using a nested case-cohort design, we examined the relationships between demographic, therapeutic, and selected cardiovascular disease risk factors among ≥1-year HCT survivors who developed cardiomyopathy before (n = 43) or after (n = 89) 1 year from HCT as compared to a randomly selected subcohort of survivors without cardiomyopathy (n = 444). Genomic data were available for 79 cases and 267 noncases. Clinical and genetic covariates were examined for association with the risk of early or late cardiomyopathy. Clinical risk factors associated with both early- and late-onset cardiomyopathy included anthracycline exposure ≥250 mg/m(2) and pre-existing hypertension. Among late-onset cardiomyopathy cases, the development of diabetes and ischemic heart disease further increased risk. We replicated several previously reported genetic associations among early-onset cardiomyopathy cases, including rs1786814 in CELF4, rs2232228 in HAS3, and rs17863783 in UGT1A6. None of these markers were associated with risk of late-onset cardiomyopathy. A combination of demographic, treatment, and clinical covariates predicted early-onset cardiomyopathy with reasonable accuracy (area under the curve [AUC], .76; 95% confidence interval [CI], .68 to .83), but prediction of late cardiomyopathy was poor (AUC, .59; 95% CI .53 to .67). The addition of genetic polymorphisms with marginal associations (odds ratios ≥1.3) did not enhance prediction for either early- or late-onset cardiomyopathy. Conventional cardiovascular risk factors influence the risk of both early- and late-onset cardiomyopathy in HCT survivors. Although certain genetic markers may influence the risk of early-onset disease, further work is required to validate previously reported findings and to determine how genetic information should be incorporated into clinically useful risk prediction models. PMID:26968791
Genetics of familial hypercholesterolemia.
Brautbar, Ariel; Leary, Emili; Rasmussen, Kristen; Wilson, Don P; Steiner, Robert D; Virani, Salim
2015-04-01
Familial hypercholesterolemia (FH) is a genetic disorder characterized by elevated low-density lipoprotein (LDL) cholesterol and premature cardiovascular disease, with a prevalence of approximately 1 in 200-500 for heterozygotes in North America and Europe. Monogenic FH is largely attributed to mutations in the LDLR, APOB, and PCSK9 genes. Differential diagnosis is critical to distinguish FH from conditions with phenotypically similar presentations to ensure appropriate therapeutic management and genetic counseling. Accurate diagnosis requires careful phenotyping based on clinical and biochemical presentation, validated by genetic testing. Recent investigations to discover additional genetic loci associated with extreme hypercholesterolemia using known FH families and population studies have met with limited success. Here, we provide a brief overview of the genetic determinants, differential diagnosis, genetic testing, and counseling of FH genetics. PMID:25712136