The Variance Composition of Firm Growth Rates

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Luiz Artur Ledur Brito

2009-04-01

Full Text Available Firms exhibit a wide variability in growth rates. This can be seen as another manifestation of the fact that firms are different from one another in several respects. This study investigated this variability using the variance components technique previously used to decompose the variance of financial performance. The main source of variation in growth rates, responsible for more than 40% of total variance, corresponds to individual, idiosyncratic firm aspects and not to industry, country, or macroeconomic conditions prevailing in specific years. Firm growth, similar to financial performance, is mostly unique to specific firms and not an industry or country related phenomenon. This finding also justifies using growth as an alternative outcome of superior firm resources and as a complementary dimension of competitive advantage. This also links this research with the resource-based view of strategy. Country was the second source of variation with around 10% of total variance. The analysis was done using the Compustat Global database with 80,320 observations, comprising 13,221 companies in 47 countries, covering the years of 1994 to 2002. It also compared the variance structure of growth to the variance structure of financial performance in the same sample.

Minimum variance and variance of outgoing quality limit MDS-1(c1, c2) plans

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Raju, C.; Vidya, R.

2016-06-01

In this article, the outgoing quality (OQ) and total inspection (TI) of multiple deferred state sampling plans MDS-1(c1,c2) are studied. It is assumed that the inspection is rejection rectification. Procedures for designing MDS-1(c1,c2) sampling plans with minimum variance of OQ and TI are developed. A procedure for obtaining a plan for a designated upper limit for the variance of the OQ (VOQL) is outlined.

Genetic analyses, phenotypic adaptability and stability in sugarcane genotypes for commercial cultivation in Pernambuco.

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Dutra Filho, J A; Junior, T C; Simões Neto, D E

2015-10-05

In the present study, we assessed the agro-industrial performance of 22 sugarcane genotypes adaptable to edaphoclimatic conditions in production microregions in the State of Pernambuco, Brazil, and we recommended the commercial cultivation of select genotypes. The variables analyzed were as follows: sucrose percentage in cane juice, tonnage of saccharose per hectare (TPH), sugarcane tonnage per hectare (TCH), fiber, solid soluble contents, total recoverable sugar tonnage (ATR), and total recoverable sugar tonnage per hectare (ATR t/ha). A randomized block design with 4 repeats was used. Combined variance of the experiments, genetic parameter estimates, and environment stratification were analyzed. Phenotypic adaptability and stability were analyzed using the Annicchiarico and Wricke methods and analysis of variance. Genetic gain was estimated using the classic index and sum of ranks. Genotype selection was efficient for TPH, TCH, and ATR t/ha. Genotypes presented a great potential for improvement and a similar response pattern in Litoral Norte and Mata Sul microregions for TPH and TCH and Litoral Norte and Litoral Sul microregions for ATR t/ha. Genotypes SP78-4764, RB813804, and SP79-101 showed better productivity and phenotypic adaptability and stability, according to the Wricke and Annicchiarico methods. These genotypes can be recommended for cultivation in the sugarcane belt in the State of Pernambuco.

Epigenetic Variance, Performing Cooperative Structure with Genetics, Is Associated with Leaf Shape Traits in Widely Distributed Populations of Ornamental Tree Prunus mume

Directory of Open Access Journals (Sweden)

Kaifeng Ma

2018-01-01

Full Text Available Increasing evidence shows that epigenetics plays an important role in phenotypic variance. However, little is known about epigenetic variation in the important ornamental tree Prunus mume. We used amplified fragment length polymorphism (AFLP and methylation-sensitive amplified polymorphism (MSAP techniques, and association analysis and sequencing to investigate epigenetic variation and its relationships with genetic variance, environment factors, and traits. By performing leaf sampling, the relative total methylation level (29.80% was detected in 96 accessions of P. mume. And the relative hemi-methylation level (15.77% was higher than the relative full methylation level (14.03%. The epigenetic diversity (I∗ = 0.575, h∗ = 0.393 was higher than the genetic diversity (I = 0.484, h = 0.319. The cultivated population displayed greater epigenetic diversity than the wild populations in both southwest and southeast China. We found that epigenetic variance and genetic variance, and environmental factors performed cooperative structures, respectively. In particular, leaf length, width and area were positively correlated with relative full methylation level and total methylation level, indicating that the DNA methylation level played a role in trait variation. In total, 203 AFLP and 423 MSAP associated markers were detected and 68 of them were sequenced. Homologous analysis and functional prediction suggested that the candidate marker-linked genes were essential for leaf morphology development and metabolism, implying that these markers play critical roles in the establishment of leaf length, width, area, and ratio of length to width.

Epigenetic Variance, Performing Cooperative Structure with Genetics, Is Associated with Leaf Shape Traits in Widely Distributed Populations of Ornamental Tree Prunus mume.

Science.gov (United States)

Ma, Kaifeng; Sun, Lidan; Cheng, Tangren; Pan, Huitang; Wang, Jia; Zhang, Qixiang

2018-01-01

Increasing evidence shows that epigenetics plays an important role in phenotypic variance. However, little is known about epigenetic variation in the important ornamental tree Prunus mume . We used amplified fragment length polymorphism (AFLP) and methylation-sensitive amplified polymorphism (MSAP) techniques, and association analysis and sequencing to investigate epigenetic variation and its relationships with genetic variance, environment factors, and traits. By performing leaf sampling, the relative total methylation level (29.80%) was detected in 96 accessions of P . mume . And the relative hemi-methylation level (15.77%) was higher than the relative full methylation level (14.03%). The epigenetic diversity ( I ∗ = 0.575, h ∗ = 0.393) was higher than the genetic diversity ( I = 0.484, h = 0.319). The cultivated population displayed greater epigenetic diversity than the wild populations in both southwest and southeast China. We found that epigenetic variance and genetic variance, and environmental factors performed cooperative structures, respectively. In particular, leaf length, width and area were positively correlated with relative full methylation level and total methylation level, indicating that the DNA methylation level played a role in trait variation. In total, 203 AFLP and 423 MSAP associated markers were detected and 68 of them were sequenced. Homologous analysis and functional prediction suggested that the candidate marker-linked genes were essential for leaf morphology development and metabolism, implying that these markers play critical roles in the establishment of leaf length, width, area, and ratio of length to width.

Identification of QTL for UV-protective eye area pigmentation in cattle by progeny phenotyping and genome-wide association analysis.

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Hubert Pausch

Full Text Available Pigmentation patterns allow for the differentiation of cattle breeds. A dominantly inherited white head is characteristic for animals of the Fleckvieh (FV breed. However, a minority of the FV animals exhibits peculiar pigmentation surrounding the eyes (ambilateral circumocular pigmentation, ACOP. In areas where animals are exposed to increased solar ultraviolet radiation, ACOP is associated with a reduced susceptibility to bovine ocular squamous cell carcinoma (BOSCC, eye cancer. Eye cancer is the most prevalent malignant tumour affecting cattle. Selection for animals with ACOP rapidly reduces the incidence of BOSCC. To identify quantitative trait loci (QTL underlying ACOP, we performed a genome-wide association study using 658,385 single nucleotide polymorphisms (SNPs. The study population consisted of 3579 bulls of the FV breed with a total of 320,186 progeny with phenotypes for ACOP. The proportion of progeny with ACOP was used as a quantitative trait with high heritability (h(2 = 0.79. A variance component based approach to account for population stratification uncovered twelve QTL regions on seven chromosomes. The identified QTL point to MCM6, PAX3, ERBB3, KITLG, LEF1, DKK2, KIT, CRIM1, ATRN, GSDMC, MITF and NBEAL2 as underlying genes for eye area pigmentation in cattle. The twelve QTL regions explain 44.96% of the phenotypic variance of the proportion of daughters with ACOP. The chromosomes harbouring significantly associated SNPs account for 54.13% of the phenotypic variance, while another 19.51% of the phenotypic variance is attributable to chromosomes without identified QTL. Thus, the missing heritability amounts to 7% only. Our results support a polygenic inheritance pattern of ACOP in cattle and provide the basis for efficient genomic selection of animals that are less susceptible to serious eye diseases.

FTO genotype is associated with phenotypic variability of body mass index

NARCIS (Netherlands)

Yang, J.; Loos, R.J.; Powell, J.E.; Medland, S.E.; Speliotes, E.K.; Chasman, D.I.; Rose, L.M.; Thorleifsson, G.; Steinthorsdottir, V.; Mägi, R.; Waite, L.; Smith, A.V.; Yerges-Armstrong, L.M.; Monda, K.L.; Hadley, D.; Mahajan, A.; Li, G.; Kapur, K.; Vitart, V.; Huffman, J.E.; Wang, S.R.; Palmer, C.; Esko, T.; Fischer, K.; Zhao, J.H.; Demirkan, A.; Isaacs, A.; Feitosa, M.F.; Luan, J.; Heard-Costa, N.L.; White, C.; Jackson, A.U.; Preuss, M; Ziegler, A.; Eriksson, J.; Kutalik, Z.; Frau, F.; Nolte, I.M.; van Vliet-Ostaptchouk, J.V.; Hottenga, J.J.; Jacobs, K.B.; Verweij, N.; Goel, A.; Medina-Gomez, C.; Estrada, K.; Bragg-Gresham, J.L.; Sanna, S.; Sidore, C.; Tyrer, J.; Teumer, A.; Prokopenko, I.; Mangino, M.; Lindgren, C.M.; Assimes, T.L.; Shuldiner, A.R.; Hui, J.; Beilby, J.P.; McArdle, W.L.; Hall, P.; Haritunians, T.; Zgaga, L.; Kolcic, I.; Polasek, O.; Zemunik, T.; Oostra, B.A.; Junttila, M.J.; Grönberg, H.; Schreiber, S; Peters, A.; Hicks, A.A.; Stephens, J.; Foad, N.S.; Laitinen, J.; Pouta, A.; Kaakinen, M.; Willemsen, G.; Vink, J.M.; Wild, S.H.; Navis, G.; Asselbergs, F.W.; Homuth, G.; John, U.; Iribarren, C.; Harris, T.; Launer, L.J.; Gudnason, V.; O'Connell, J.R.; Boerwinkle, E.; Cadby, G.; Palmer, L.J.; James, A.L.; Musk, A.W.; Ingelsson, E.; Psaty, B.M.; Beckmann, J.S.; Waeber, G.; Vollenweider, P.; Hayward, C.; Wright, A.F.; Rudan, I.; Groop, L.C.; Metspalu, A.; Thee Khaw, K.; van Duijn, C.M.; Borecki, I.B.; Province, M.A.; Wareham, N.J.; Tardif, J.C.; Huikuri, H.V.; Cupples, L.A.; Atwood, L.D.; Fox, C.S.; Boehnke, M.; Collins, F.S.; Mohlke, K.L.; Erdmann, J.; Schunkert, H.; Hengstenberg, C.; Stark, K.; Lorentzon, M.; Ohlsson, C.; Cusi, D.; Staessen, J.A.; van der Klauw, M.M.; Pramstaller, P.P.; Kathiresan, S.; Jolley, D.J.; Ripatti, S.; Jarvelin, M.-R.; de Geus, E.J.C.; Boomsma, D.I.; Penninx, B.W.J.H.; Wilson, J.F.; Campbell, H.; Chanock, S.J.; van der Harst, P.; Hamsten, A.; Watkins, H.; Hofman, A.; Witteman, J.C.; Zillikens, M.C.; Uitterlinden, A.G.; Rivadeneira, F.; Kiemeney, L.A.; Vermeulen, S.H.; Abecasis, G.R.; Schlessinger, D.; Schipf, S.; Stumvoll, M.; Tönjes, A.; Spector, T.D.; North, K.E.; Lettre, G.; McCarthy, M.I.; Berndt, S.I.; Heath, A.C.; Madden, P.A.F.; Nyholt, DR; Montgomery, G.W.; Martin, N.G.; McKnight, B.; Strachan, D.P.; Hill, W.G.; Snieder, H.; Ridker, P.M.; Thorsteinsdottir, U.; Stefansson, K.; Frayling, T.M.; Hirschhorn, J.N.; Goddard, M.E.; Visscher, P.M.

2012-01-01

There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human

Estimation of additive and dominance variance for reproductive traits from different models in Duroc purebred

Directory of Open Access Journals (Sweden)

Talerngsak Angkuraseranee

2010-05-01

Full Text Available The additive and dominance genetic variances of 5,801 Duroc reproductive and growth records were estimated usingBULPF90 PC-PACK. Estimates were obtained for number born alive (NBA, birth weight (BW, number weaned (NW, andweaning weight (WW. Data were analyzed using two mixed model equations. The first model included fixed effects andrandom effects identifying inbreeding depression, additive gene effect and permanent environments effects. The secondmodel was similar to the first model, but included the dominance genotypic effect. Heritability estimates of NBA, BW, NWand WW from the two models were 0.1558/0.1716, 0.1616/0.1737, 0.0372/0.0874 and 0.1584/0.1516 respectively. Proportionsof dominance effect to total phenotypic variance from the dominance model were 0.1024, 0.1625, 0.0470, and 0.1536 for NBA,BW, NW and WW respectively. Dominance effects were found to have sizable influence on the litter size traits analyzed.Therefore, genetic evaluation with the dominance model (Model 2 is found more appropriate than the animal model (Model 1.

Reduced genetic variance among high fitness individuals: inferring stabilizing selection on male sexual displays in Drosophila serrata.

Science.gov (United States)

Sztepanacz, Jacqueline L; Rundle, Howard D

2012-10-01

Directional selection is prevalent in nature, yet phenotypes tend to remain relatively constant, suggesting a limit to trait evolution. However, the genetic basis of this limit is unresolved. Given widespread pleiotropy, opposing selection on a trait may arise from the effects of the underlying alleles on other traits under selection, generating net stabilizing selection on trait genetic variance. These pleiotropic costs of trait exaggeration may arise through any number of other traits, making them hard to detect in phenotypic analyses. Stabilizing selection can be inferred, however, if genetic variance is greater among low- compared to high-fitness individuals. We extend a recently suggested approach to provide a direct test of a difference in genetic variance for a suite of cuticular hydrocarbons (CHCs) in Drosophila serrata. Despite strong directional sexual selection on these traits, genetic variance differed between high- and low-fitness individuals and was greater among the low-fitness males for seven of eight CHCs, significantly more than expected by chance. Univariate tests of a difference in genetic variance were nonsignificant but likely have low power. Our results suggest that further CHC exaggeration in D. serrata in response to sexual selection is limited by pleiotropic costs mediated through other traits. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Local variances in biomonitoring

International Nuclear Information System (INIS)

Wolterbeek, H.T.

1999-01-01

The present study deals with the (larger-scaled) biomonitoring survey and specifically focuses on the sampling site. In most surveys, the sampling site is simply selected or defined as a spot of (geographical) dimensions which is small relative to the dimensions of the total survey area. Implicitly it is assumed that the sampling site is essentially homogeneous with respect to the investigated variation in survey parameters. As such, the sampling site is mostly regarded as 'the basic unit' of the survey. As a logical consequence, the local (sampling site) variance should also be seen as a basic and important characteristic of the survey. During the study, work is carried out to gain more knowledge of the local variance. Multiple sampling is carried out at a specific site (tree bark, mosses, soils), multi-elemental analyses are carried out by NAA, and local variances are investigated by conventional statistics, factor analytical techniques, and bootstrapping. Consequences of the outcomes are discussed in the context of sampling, sample handling and survey quality. (author)

Directional selection effects on patterns of phenotypic (co)variation in wild populations.

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Assis, A P A; Patton, J L; Hubbe, A; Marroig, G

2016-11-30

Phenotypic (co)variation is a prerequisite for evolutionary change, and understanding how (co)variation evolves is of crucial importance to the biological sciences. Theoretical models predict that under directional selection, phenotypic (co)variation should evolve in step with the underlying adaptive landscape, increasing the degree of correlation among co-selected traits as well as the amount of genetic variance in the direction of selection. Whether either of these outcomes occurs in natural populations is an open question and thus an important gap in evolutionary theory. Here, we documented changes in the phenotypic (co)variation structure in two separate natural populations in each of two chipmunk species (Tamias alpinus and T. speciosus) undergoing directional selection. In populations where selection was strongest (those of T. alpinus), we observed changes, at least for one population, in phenotypic (co)variation that matched theoretical expectations, namely an increase of both phenotypic integration and (co)variance in the direction of selection and a re-alignment of the major axis of variation with the selection gradient. © 2016 The Author(s).

The derivative based variance sensitivity analysis for the distribution parameters and its computation

International Nuclear Information System (INIS)

Wang, Pan; Lu, Zhenzhou; Ren, Bo; Cheng, Lei

2013-01-01

The output variance is an important measure for the performance of a structural system, and it is always influenced by the distribution parameters of inputs. In order to identify the influential distribution parameters and make it clear that how those distribution parameters influence the output variance, this work presents the derivative based variance sensitivity decomposition according to Sobol′s variance decomposition, and proposes the derivative based main and total sensitivity indices. By transforming the derivatives of various orders variance contributions into the form of expectation via kernel function, the proposed main and total sensitivity indices can be seen as the “by-product” of Sobol′s variance based sensitivity analysis without any additional output evaluation. Since Sobol′s variance based sensitivity indices have been computed efficiently by the sparse grid integration method, this work also employs the sparse grid integration method to compute the derivative based main and total sensitivity indices. Several examples are used to demonstrate the rationality of the proposed sensitivity indices and the accuracy of the applied method

Origin and consequences of the relationship between protein mean and variance.

Science.gov (United States)

Vallania, Francesco Luigi Massimo; Sherman, Marc; Goodwin, Zane; Mogno, Ilaria; Cohen, Barak Alon; Mitra, Robi David

2014-01-01

Cell-to-cell variance in protein levels (noise) is a ubiquitous phenomenon that can increase fitness by generating phenotypic differences within clonal populations of cells. An important challenge is to identify the specific molecular events that control noise. This task is complicated by the strong dependence of a protein's cell-to-cell variance on its mean expression level through a power-law like relationship (σ2∝μ1.69). Here, we dissect the nature of this relationship using a stochastic model parameterized with experimentally measured values. This framework naturally recapitulates the power-law like relationship (σ2∝μ1.6) and accurately predicts protein variance across the yeast proteome (r2 = 0.935). Using this model we identified two distinct mechanisms by which protein variance can be increased. Variables that affect promoter activation, such as nucleosome positioning, increase protein variance by changing the exponent of the power-law relationship. In contrast, variables that affect processes downstream of promoter activation, such as mRNA and protein synthesis, increase protein variance in a mean-dependent manner following the power-law. We verified our findings experimentally using an inducible gene expression system in yeast. We conclude that the power-law-like relationship between noise and protein mean is due to the kinetics of promoter activation. Our results provide a framework for understanding how molecular processes shape stochastic variation across the genome.

Variance in total levels of phospholipase C zeta (PLC-ζ) in human sperm may limit the applicability of quantitative immunofluorescent analysis as a diagnostic indicator of oocyte activation capability.

Science.gov (United States)

Kashir, Junaid; Jones, Celine; Mounce, Ginny; Ramadan, Walaa M; Lemmon, Bernadette; Heindryckx, Bjorn; de Sutter, Petra; Parrington, John; Turner, Karen; Child, Tim; McVeigh, Enda; Coward, Kevin

2013-01-01

To examine whether similar levels of phospholipase C zeta (PLC-ζ) protein are present in sperm from men whose ejaculates resulted in normal oocyte activation, and to examine whether a predominant pattern of PLC-ζ localization is linked to normal oocyte activation ability. Laboratory study. University laboratory. Control subjects (men with proven oocyte activation capacity; n = 16) and men whose sperm resulted in recurrent intracytoplasmic sperm injection failure (oocyte activation deficient [OAD]; n = 5). Quantitative immunofluorescent analysis of PLC-ζ protein in human sperm. Total levels of PLC-ζ fluorescence, proportions of sperm exhibiting PLC-ζ immunoreactivity, and proportions of PLC-ζ localization patterns in sperm from control and OAD men. Sperm from control subjects presented a significantly higher proportion of sperm exhibiting PLC-ζ immunofluorescence compared with infertile men diagnosed with OAD (82.6% and 27.4%, respectively). Total levels of PLC-ζ in sperm from individual control and OAD patients exhibited significant variance, with sperm from 10 out of 16 (62.5%) exhibiting levels similar to OAD samples. Predominant PLC-ζ localization patterns varied between control and OAD samples with no predictable or consistent pattern. The results indicate that sperm from control men exhibited significant variance in total levels of PLC-ζ protein, as well as significant variance in the predominant localization pattern. Such variance may hinder the diagnostic application of quantitative PLC-ζ immunofluorescent analysis. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Candidate gene analyses of 3-dimensional dentoalveolar phenotypes in subjects with malocclusion.

Science.gov (United States)

Weaver, Cole A; Miller, Steven F; da Fontoura, Clarissa S G; Wehby, George L; Amendt, Brad A; Holton, Nathan E; Allareddy, Veeratrishul; Southard, Thomas E; Moreno Uribe, Lina M

2017-03-01

Genetic studies of malocclusion etiology have identified 4 deleterious mutations in genes DUSP6,ARHGAP21, FGF23, and ADAMTS1 in familial Class III cases. Although these variants may have large impacts on Class III phenotypic expression, their low frequency (common genetic variations in craniofacial candidate genes and 3-dimensional dentoalveolar phenotypes in patients with malocclusion. Pretreatment dental casts or cone-beam computed tomographic images from 300 healthy subjects were digitized with 48 landmarks. The 3-dimensional coordinate data were submitted to a geometric morphometric approach along with principal component analysis to generate continuous phenotypes including symmetric and asymmetric components of dentoalveolar shape variation, fluctuating asymmetry, and size. The subjects were genotyped for 222 single-nucleotide polymorphisms in 82 genes/loci, and phenotpye-genotype associations were tested via multivariate linear regression. Principal component analysis of symmetric variation identified 4 components that explained 68% of the total variance and depicted anteroposterior, vertical, and transverse dentoalveolar discrepancies. Suggestive associations (P centroid size, a proxy for dentoalveolar size variation with 4p16.1 and SNAI1. Specific genetic pathways associated with 3-dimensional dentoalveolar phenotypic variation in malocclusions were identified. Copyright © 2016 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

The quantitative genetics of phenotypic variation in animals

NARCIS (Netherlands)

Hill, W.G.; Mulder, H.A.; Zhang, X.S.

2007-01-01

Considerable attention has been paid to estimating genetic variability in quantitative traits and to how it is maintained and changed by selection in natural and domesticated populations, but rather little attention has been paid to how levels of environmental and phenotypic variance are influenced.

Variance components for body weight in Japanese quails (Coturnix japonica

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RO Resende

2005-03-01

Full Text Available The objective of this study was to estimate the variance components for body weight in Japanese quails by Bayesian procedures. The body weight at hatch (BWH and at 7 (BW07, 14 (BW14, 21 (BW21 and 28 days of age (BW28 of 3,520 quails was recorded from August 2001 to June 2002. A multiple-trait animal model with additive genetic, maternal environment and residual effects was implemented by Gibbs sampling methodology. A single Gibbs sampling with 80,000 rounds was generated by the program MTGSAM (Multiple Trait Gibbs Sampling in Animal Model. Normal and inverted Wishart distributions were used as prior distributions for the random effects and the variance components, respectively. Variance components were estimated based on the 500 samples that were left after elimination of 30,000 rounds in the burn-in period and 100 rounds of each thinning interval. The posterior means of additive genetic variance components were 0.15; 4.18; 14.62; 27.18 and 32.68; the posterior means of maternal environment variance components were 0.23; 1.29; 2.76; 4.12 and 5.16; and the posterior means of residual variance components were 0.084; 6.43; 22.66; 31.21 and 30.85, at hatch, 7, 14, 21 and 28 days old, respectively. The posterior means of heritability were 0.33; 0.35; 0.36; 0.43 and 0.47 at hatch, 7, 14, 21 and 28 days old, respectively. These results indicate that heritability increased with age. On the other hand, after hatch there was a marked reduction in the maternal environment variance proportion of the phenotypic variance, whose estimates were 0.50; 0.11; 0.07; 0.07 and 0.08 for BWH, BW07, BW14, BW21 and BW28, respectively. The genetic correlation between weights at different ages was high, except for those estimates between BWH and weight at other ages. Changes in body weight of quails can be efficiently achieved by selection.

Unraveling the genetic architecture of environmental variance of somatic cell score using high-density single nucleotide polymorphism and cow data from experimental farms

NARCIS (Netherlands)

Mulder, H.A.; Crump, R.E.; Calus, M.P.L.; Veerkamp, R.F.

2013-01-01

In recent years, it has been shown that not only is the phenotype under genetic control, but also the environmental variance. Very little, however, is known about the genetic architecture of environmental variance. The main objective of this study was to unravel the genetic architecture of the mean

Phenotypic and Genetic Effects of Contrasting Ethanol Environments on Physiological and Developmental Traits in Drosophila melanogaster

Science.gov (United States)

Castañeda, Luis E.; Nespolo, Roberto F.

2013-01-01

A central problem in evolutionary physiology is to understand the relationship between energy metabolism and fitness-related traits. Most attempts to do so have been based on phenotypic correlations that are not informative for the evolutionary potential of natural populations. Here, we explored the effect of contrasting ethanol environments on physiological and developmental traits, their genetic (co)variances and genetic architecture in Drosophila melanogaster. Phenotypic and genetic parameters were estimated in two populations (San Fernando and Valdivia, Chile), using a half-sib family design where broods were split into ethanol-free and ethanol-supplemented conditions. Our findings show that metabolic rate, body mass and development times were sensitive (i.e., phenotypic plasticity) to ethanol conditions and dependent on population origin. Significant heritabilities were found for all traits, while significant genetic correlations were only found between larval and total development time and between development time and metabolic rate for flies of the San Fernando population developed in ethanol-free conditions. Posterior analyses indicated that the G matrices differed between ethanol conditions for the San Fernando population (mainly explained by differences in genetic (co)variances of developmental traits), whereas the Valdivia population exhibited similar G matrices between ethanol conditions. Our findings suggest that ethanol-free environment increases the energy available to reduce development time. Therefore, our results indicate that environmental ethanol could modify the process of energy allocation, which could have consequences on the evolutionary response of natural populations of D. melanogaster. PMID:23505567

Longitudinal Investigation into Genetics in the Conservation of Metabolic Phenotypes in Danish and Chinese Twins

DEFF Research Database (Denmark)

Li, Shuxia; Kyvik, Kirsten Ohm; Duan, Haiping

2016-01-01

twin study on long-term stability of metabolic phenotypes in Danish and Chinese twins identified a common pattern of high genetic control over phenotype conservation, and at the same time revealed population-specific patterns of genetic and common environmental regulation on the variance as well...

Assessment of metabolic phenotypic variability in children’s urine using 1H NMR spectroscopy

Science.gov (United States)

Maitre, Léa; Lau, Chung-Ho E.; Vizcaino, Esther; Robinson, Oliver; Casas, Maribel; Siskos, Alexandros P.; Want, Elizabeth J.; Athersuch, Toby; Slama, Remy; Vrijheid, Martine; Keun, Hector C.; Coen, Muireann

2017-04-01

The application of metabolic phenotyping in clinical and epidemiological studies is limited by a poor understanding of inter-individual, intra-individual and temporal variability in metabolic phenotypes. Using 1H NMR spectroscopy we characterised short-term variability in urinary metabolites measured from 20 children aged 8-9 years old. Daily spot morning, night-time and pooled (50:50 morning and night-time) urine samples across six days (18 samples per child) were analysed, and 44 metabolites quantified. Intraclass correlation coefficients (ICC) and mixed effect models were applied to assess the reproducibility and biological variance of metabolic phenotypes. Excellent analytical reproducibility and precision was demonstrated for the 1H NMR spectroscopic platform (median CV 7.2%). Pooled samples captured the best inter-individual variability with an ICC of 0.40 (median). Trimethylamine, N-acetyl neuraminic acid, 3-hydroxyisobutyrate, 3-hydroxybutyrate/3-aminoisobutyrate, tyrosine, valine and 3-hydroxyisovalerate exhibited the highest stability with over 50% of variance specific to the child. The pooled sample was shown to capture the most inter-individual variance in the metabolic phenotype, which is of importance for molecular epidemiology study design. A substantial proportion of the variation in the urinary metabolome of children is specific to the individual, underlining the potential of such data to inform clinical and exposome studies conducted early in life.

Estimating the variation, autocorrelation, and environmental sensitivity of phenotypic selection

NARCIS (Netherlands)

Chevin, Luis-Miguel; Visser, Marcel E.; Tufto, Jarle

2015-01-01

Despite considerable interest in temporal and spatial variation of phenotypic selection, very few methods allow quantifying this variation while correctly accounting for the error variance of each individual estimate. Furthermore, the available methods do not estimate the autocorrelation of

Estimating the variation, autocorrelation, and environmental sensitivity of phenotypic selection

NARCIS (Netherlands)

Chevin, Luis-Miguel; Visser, Marcel E.; Tufto, Jarle

Despite considerable interest in temporal and spatial variation of phenotypic selection, very few methods allow quantifying this variation while correctly accounting for the error variance of each individual estimate. Furthermore, the available methods do not estimate the autocorrelation of

Rethinking the evolution of specialization: A model for the evolution of phenotypic heterogeneity.

Science.gov (United States)

Rubin, Ilan N; Doebeli, Michael

2017-12-21

Phenotypic heterogeneity refers to genetically identical individuals that express different phenotypes, even when in the same environment. Traditionally, "bet-hedging" in fluctuating environments is offered as the explanation for the evolution of phenotypic heterogeneity. However, there are an increasing number of examples of microbial populations that display phenotypic heterogeneity in stable environments. Here we present an evolutionary model of phenotypic heterogeneity of microbial metabolism and a resultant theory for the evolution of phenotypic versus genetic specialization. We use two-dimensional adaptive dynamics to track the evolution of the population phenotype distribution of the expression of two metabolic processes with a concave trade-off. Rather than assume a Gaussian phenotype distribution, we use a Beta distribution that is capable of describing genotypes that manifest as individuals with two distinct phenotypes. Doing so, we find that environmental variation is not a necessary condition for the evolution of phenotypic heterogeneity, which can evolve as a form of specialization in a stable environment. There are two competing pressures driving the evolution of specialization: directional selection toward the evolution of phenotypic heterogeneity and disruptive selection toward genetically determined specialists. Because of the lack of a singular point in the two-dimensional adaptive dynamics and the fact that directional selection is a first order process, while disruptive selection is of second order, the evolution of phenotypic heterogeneity dominates and often precludes speciation. We find that branching, and therefore genetic specialization, occurs mainly under two conditions: the presence of a cost to maintaining a high phenotypic variance or when the effect of mutations is large. A cost to high phenotypic variance dampens the strength of selection toward phenotypic heterogeneity and, when sufficiently large, introduces a singular point into

Continuous-Time Mean-Variance Portfolio Selection under the CEV Process

Directory of Open Access Journals (Sweden)

Hui-qiang Ma

2014-01-01

Full Text Available We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance efficient frontier analytically. The results show that the mean-variance efficient frontier is still a parabola in the mean-variance plane, and the optimal strategies depend not only on the total wealth but also on the stock price. Moreover, some numerical examples are given to analyze the sensitivity of the efficient frontier with respect to the elasticity parameter and to illustrate the results presented in this paper. The numerical results show that the price of risk decreases as the elasticity coefficient increases.

Genetic heterogeneity of within-family variance of body weight in Atlantic salmon (Salmo salar).

Science.gov (United States)

Sonesson, Anna K; Odegård, Jørgen; Rönnegård, Lars

2013-10-17

Canalization is defined as the stability of a genotype against minor variations in both environment and genetics. Genetic variation in degree of canalization causes heterogeneity of within-family variance. The aims of this study are twofold: (1) quantify genetic heterogeneity of (within-family) residual variance in Atlantic salmon and (2) test whether the observed heterogeneity of (within-family) residual variance can be explained by simple scaling effects. Analysis of body weight in Atlantic salmon using a double hierarchical generalized linear model (DHGLM) revealed substantial heterogeneity of within-family variance. The 95% prediction interval for within-family variance ranged from ~0.4 to 1.2 kg2, implying that the within-family variance of the most extreme high families is expected to be approximately three times larger than the extreme low families. For cross-sectional data, DHGLM with an animal mean sub-model resulted in severe bias, while a corresponding sire-dam model was appropriate. Heterogeneity of variance was not sensitive to Box-Cox transformations of phenotypes, which implies that heterogeneity of variance exists beyond what would be expected from simple scaling effects. Substantial heterogeneity of within-family variance was found for body weight in Atlantic salmon. A tendency towards higher variance with higher means (scaling effects) was observed, but heterogeneity of within-family variance existed beyond what could be explained by simple scaling effects. For cross-sectional data, using the animal mean sub-model in the DHGLM resulted in biased estimates of variance components, which differed substantially both from a standard linear mean animal model and a sire-dam DHGLM model. Although genetic differences in canalization were observed, selection for increased canalization is difficult, because there is limited individual information for the variance sub-model, especially when based on cross-sectional data. Furthermore, potential macro

Speeding up microevolution: the effects of increasing temperature on selection and genetic variance in a wild bird population

NARCIS (Netherlands)

Husby, A.; Visser, M.E.; Kruuk, L.E.B.

2011-01-01

The amount of genetic variance underlying a phenotypic trait and the strength of selection acting on that trait are two key parameters that determine any evolutionary response to selection. Despite substantial evidence that, in natural populations, both parameters may vary across environmental

Genetic parameters, phenotypic, genotypic and environmental correlations and genetic variability on sunflower in the Brazilian Savannah

Directory of Open Access Journals (Sweden)

Ellen Grippi Lira

Full Text Available ABSTRACT: Sunflower (Helianthus annuus L. is an annual crop that stands out for its production of high quality oil and for an efficient selection, being necessary to estimate the components of genetic and phenotypic variance. This study aimed to estimate genetic parameters, phenotypic, genotypic and environmental correlations and genetic variability on sunflower in the Brazilian Savannah, evaluating the characters grain yield (YIELD, days to start flowering (DFL based on flowering date in R5, chapter length (CL, weight of a thousand achenes (WTA, plant height (H and oil content (OilC of 16 sunflower genotypes. The experiment was conducted at Embrapa Cerrados, Planaltina, DF, situated at 15º 35’ 30”S latitude, 47º 42’ 30”W longitude and 1.007m above sea level, in soil classified as dystroferric Oxisol. The experimental design used was a complete randomized block with four replicates. The nature for the effects of genotypes and blocks was fixed. Except for the character chapter length, genetic variance was the main component of the phenotypic variance among the genotypes, indicating high genetic variability and experimental efficiency with proper environmental control. In absolute terms, the genetic correlations were superior to phenotypic and environmental. The high values reported for heritability and selective accuracy indicated efficiency of phenotypic selection. Results showed high genetic variability among genotypes, which may contribute to the genetic improvement of sunflower.

Unraveling the genetic architecture of environmental variance of somatic cell score using high-density single nucleotide polymorphism and cow data from experimental farms.

Science.gov (United States)

Mulder, H A; Crump, R E; Calus, M P L; Veerkamp, R F

2013-01-01

In recent years, it has been shown that not only is the phenotype under genetic control, but also the environmental variance. Very little, however, is known about the genetic architecture of environmental variance. The main objective of this study was to unravel the genetic architecture of the mean and environmental variance of somatic cell score (SCS) by identifying genome-wide associations for mean and environmental variance of SCS in dairy cows and by quantifying the accuracy of genome-wide breeding values. Somatic cell score was used because previous research has shown that the environmental variance of SCS is partly under genetic control and reduction of the variance of SCS by selection is desirable. In this study, we used 37,590 single nucleotide polymorphism (SNP) genotypes and 46,353 test-day records of 1,642 cows at experimental research farms in 4 countries in Europe. We used a genomic relationship matrix in a double hierarchical generalized linear model to estimate genome-wide breeding values and genetic parameters. The estimated mean and environmental variance per cow was used in a Bayesian multi-locus model to identify SNP associated with either the mean or the environmental variance of SCS. Based on the obtained accuracy of genome-wide breeding values, 985 and 541 independent chromosome segments affecting the mean and environmental variance of SCS, respectively, were identified. Using a genomic relationship matrix increased the accuracy of breeding values relative to using a pedigree relationship matrix. In total, 43 SNP were significantly associated with either the mean (22) or the environmental variance of SCS (21). The SNP with the highest Bayes factor was on chromosome 9 (Hapmap31053-BTA-111664) explaining approximately 3% of the genetic variance of the environmental variance of SCS. Other significant SNP explained less than 1% of the genetic variance. It can be concluded that fewer genomic regions affect the environmental variance of SCS than the

Using variance structure to quantify responses to perturbation in fish catches

Science.gov (United States)

Vidal, Tiffany E.; Irwin, Brian J.; Wagner, Tyler; Rudstam, Lars G.; Jackson, James R.; Bence, James R.

2017-01-01

We present a case study evaluation of gill-net catches of Walleye Sander vitreus to assess potential effects of large-scale changes in Oneida Lake, New York, including the disruption of trophic interactions by double-crested cormorants Phalacrocorax auritus and invasive dreissenid mussels. We used the empirical long-term gill-net time series and a negative binomial linear mixed model to partition the variability in catches into spatial and coherent temporal variance components, hypothesizing that variance partitioning can help quantify spatiotemporal variability and determine whether variance structure differs before and after large-scale perturbations. We found that the mean catch and the total variability of catches decreased following perturbation but that not all sampling locations responded in a consistent manner. There was also evidence of some spatial homogenization concurrent with a restructuring of the relative productivity of individual sites. Specifically, offshore sites generally became more productive following the estimated break point in the gill-net time series. These results provide support for the idea that variance structure is responsive to large-scale perturbations; therefore, variance components have potential utility as statistical indicators of response to a changing environment more broadly. The modeling approach described herein is flexible and would be transferable to other systems and metrics. For example, variance partitioning could be used to examine responses to alternative management regimes, to compare variability across physiographic regions, and to describe differences among climate zones. Understanding how individual variance components respond to perturbation may yield finer-scale insights into ecological shifts than focusing on patterns in the mean responses or total variability alone.

Downside Variance Risk Premium

OpenAIRE

Feunou, Bruno; Jahan-Parvar, Mohammad; Okou, Cedric

2015-01-01

We propose a new decomposition of the variance risk premium in terms of upside and downside variance risk premia. The difference between upside and downside variance risk premia is a measure of skewness risk premium. We establish that the downside variance risk premium is the main component of the variance risk premium, and that the skewness risk premium is a priced factor with significant prediction power for aggregate excess returns. Our empirical investigation highlights the positive and s...

Effect of captivity on genetic variance for five traits in the large milkweed bug (Oncopeltus fasciatus).

Science.gov (United States)

Rodríguez-Clark, K M

2004-07-01

Understanding the changes in genetic variance which may occur as populations move from nature into captivity has been considered important when populations in captivity are used as models of wild ones. However, the inherent significance of these changes has not previously been appreciated in a conservation context: are the methods aimed at founding captive populations with gene diversity representative of natural populations likely also to capture representative quantitative genetic variation? Here, I investigate changes in heritability and a less traditional measure, evolvability, between nature and captivity for the large milkweed bug, Oncopeltus fasciatus, to address this question. Founders were collected from a 100-km transect across the north-eastern US, and five traits (wing colour, pronotum colour, wing length, early fecundity and later fecundity) were recorded for founders and for their offspring during two generations in captivity. Analyses reveal significant heritable variation for some life history and morphological traits in both environments, with comparable absolute levels of evolvability across all traits (0-30%). Randomization tests show that while changes in heritability and total phenotypic variance were highly variable, additive genetic variance and evolvability remained stable across the environmental transition in the three morphological traits (changing 1-2% or less), while they declined significantly in the two life-history traits (5-8%). Although it is unclear whether the declines were due to selection or gene-by-environment interactions (or both), such declines do not appear inevitable: captive populations with small numbers of founders may contain substantial amounts of the evolvability found in nature, at least for some traits.

Phenotypic correlations between egg weight and some egg quality ...

African Journals Online (AJOL)

Eggs were examined for both internal and external egg quality traits.Data obtained were subjected to one-way analysis of variance using the general linear procedure of SAS (2012). Differences in means were ranked using the Duncan's multiple Range test. Phenotypic correlations between egg weight and other egg quality ...

Meta-analysis of SNPs involved in variance heterogeneity using Levene's test for equal variances

Science.gov (United States)

Deng, Wei Q; Asma, Senay; Paré, Guillaume

2014-01-01

Meta-analysis is a commonly used approach to increase the sample size for genome-wide association searches when individual studies are otherwise underpowered. Here, we present a meta-analysis procedure to estimate the heterogeneity of the quantitative trait variance attributable to genetic variants using Levene's test without needing to exchange individual-level data. The meta-analysis of Levene's test offers the opportunity to combine the considerable sample size of a genome-wide meta-analysis to identify the genetic basis of phenotypic variability and to prioritize single-nucleotide polymorphisms (SNPs) for gene–gene and gene–environment interactions. The use of Levene's test has several advantages, including robustness to departure from the normality assumption, freedom from the influence of the main effects of SNPs, and no assumption of an additive genetic model. We conducted a meta-analysis of the log-transformed body mass index of 5892 individuals and identified a variant with a highly suggestive Levene's test P-value of 4.28E-06 near the NEGR1 locus known to be associated with extreme obesity. PMID:23921533

Candidate gene analyses of 3-dimensional dentoalveolar phenotypes in subjects with malocclusion

Science.gov (United States)

Weaver, Cole A.; Miller, Steven F.; da Fontoura, Clarissa S. G.; Wehby, George L.; Amendt, Brad A.; Holton, Nathan E.; Allareddy, Veeratrishul; Southard, Thomas E.; Moreno Uribe, Lina M.

2017-01-01

Introduction Genetic studies of malocclusion etiology have identified 4 deleterious mutations in genes, DUSP6, ARHGAP21, FGF23, and ADAMTS1 in familial Class III cases. Although these variants may have large impacts on Class III phenotypic expression, their low frequency (malocclusions. Thus, much of the genetic variation underlying the dentofacial phenotypic variation associated with malocclusion remains unknown. In this study, we evaluated associations between common genetic variations in craniofacial candidate genes and 3-dimensional dentoalveolar phenotypes in patients with malocclusion. Methods Pretreatment dental casts or cone-beam computed tomographic images from 300 healthy subjects were digitized with 48 landmarks. The 3-dimensional coordinate data were submitted to a geometric morphometric approach along with principal component analysis to generate continuous phenotypes including symmetric and asymmetric components of dentoalveolar shape variation, fluctuating asymmetry, and size. The subjects were genotyped for 222 single-nucleotide polymorphisms in 82 genes/loci, and phenotpye-genotype associations were tested via multivariate linear regression. Results Principal component analysis of symmetric variation identified 4 components that explained 68% of the total variance and depicted anteroposterior, vertical, and transverse dentoalveolar discrepancies. Suggestive associations (P eruptions. Suggestive associations were found with TBX1 AJUBA, SNAI3 SATB2, TP63, and 1p22.1. Fluctuating asymmetry was associated with BMP3 and LATS1. Associations for SATB2 and BMP3 with asymmetric variations remained significant after the Bonferroni correction (P malocclusions were identified. PMID:28257739

R package MVR for Joint Adaptive Mean-Variance Regularization and Variance Stabilization.

Science.gov (United States)

Dazard, Jean-Eudes; Xu, Hua; Rao, J Sunil

2011-01-01

We present an implementation in the R language for statistical computing of our recent non-parametric joint adaptive mean-variance regularization and variance stabilization procedure. The method is specifically suited for handling difficult problems posed by high-dimensional multivariate datasets ( p ≫ n paradigm), such as in 'omics'-type data, among which are that the variance is often a function of the mean, variable-specific estimators of variances are not reliable, and tests statistics have low powers due to a lack of degrees of freedom. The implementation offers a complete set of features including: (i) normalization and/or variance stabilization function, (ii) computation of mean-variance-regularized t and F statistics, (iii) generation of diverse diagnostic plots, (iv) synthetic and real 'omics' test datasets, (v) computationally efficient implementation, using C interfacing, and an option for parallel computing, (vi) manual and documentation on how to setup a cluster. To make each feature as user-friendly as possible, only one subroutine per functionality is to be handled by the end-user. It is available as an R package, called MVR ('Mean-Variance Regularization'), downloadable from the CRAN.

Estimating additive and non-additive genetic variances and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers.

Directory of Open Access Journals (Sweden)

Guosheng Su

Full Text Available Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1 a simple additive genetic model (MA, 2 a model including both additive and additive by additive epistatic genetic effects (MAE, 3 a model including both additive and dominance genetic effects (MAD, and 4 a full model including all three genetic components (MAED. Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions.

Estimation of measurement variances

International Nuclear Information System (INIS)

Anon.

1981-01-01

In the previous two sessions, it was assumed that the measurement error variances were known quantities when the variances of the safeguards indices were calculated. These known quantities are actually estimates based on historical data and on data generated by the measurement program. Session 34 discusses how measurement error parameters are estimated for different situations. The various error types are considered. The purpose of the session is to enable participants to: (1) estimate systematic error variances from standard data; (2) estimate random error variances from data as replicate measurement data; (3) perform a simple analysis of variances to characterize the measurement error structure when biases vary over time

Simulation study on heterogeneous variance adjustment for observations with different measurement error variance

DEFF Research Database (Denmark)

Pitkänen, Timo; Mäntysaari, Esa A; Nielsen, Ulrik Sander

2013-01-01

of variance correction is developed for the same observations. As automated milking systems are becoming more popular the current evaluation model needs to be enhanced to account for the different measurement error variances of observations from automated milking systems. In this simulation study different...... models and different approaches to account for heterogeneous variance when observations have different measurement error variances were investigated. Based on the results we propose to upgrade the currently applied models and to calibrate the heterogeneous variance adjustment method to yield same genetic......The Nordic Holstein yield evaluation model describes all available milk, protein and fat test-day yields from Denmark, Finland and Sweden. In its current form all variance components are estimated from observations recorded under conventional milking systems. Also the model for heterogeneity...

Age-dependent changes in mean and variance of gene expression across tissues in a twin cohort.

Science.gov (United States)

Viñuela, Ana; Brown, Andrew A; Buil, Alfonso; Tsai, Pei-Chien; Davies, Matthew N; Bell, Jordana T; Dermitzakis, Emmanouil T; Spector, Timothy D; Small, Kerrin S

2018-02-15

Changes in the mean and variance of gene expression with age have consequences for healthy aging and disease development. Age-dependent changes in phenotypic variance have been associated with a decline in regulatory functions leading to increase in disease risk. Here, we investigate age-related mean and variance changes in gene expression measured by RNA-seq of fat, skin, whole blood and derived lymphoblastoid cell lines (LCLs) expression from 855 adult female twins. We see evidence of up to 60% of age effects on transcription levels shared across tissues, and 47% of those on splicing. Using gene expression variance and discordance between genetically identical MZ twin pairs, we identify 137 genes with age-related changes in variance and 42 genes with age-related discordance between co-twins; implying the latter are driven by environmental effects. We identify four eQTLs whose effect on expression is age-dependent (FDR 5%). Combined, these results show a complicated mix of environmental and genetically driven changes in expression with age. Using the twin structure in our data, we show that additive genetic effects explain considerably more of the variance in gene expression than aging, but less that other environmental factors, potentially explaining why reliable expression-derived biomarkers for healthy-aging have proved elusive compared with those derived from methylation. © The Author(s) 2017. Published by Oxford University Press.

A COSMIC VARIANCE COOKBOOK

International Nuclear Information System (INIS)

Moster, Benjamin P.; Rix, Hans-Walter; Somerville, Rachel S.; Newman, Jeffrey A.

2011-01-01

Deep pencil beam surveys ( 2 ) are of fundamental importance for studying the high-redshift universe. However, inferences about galaxy population properties (e.g., the abundance of objects) are in practice limited by 'cosmic variance'. This is the uncertainty in observational estimates of the number density of galaxies arising from the underlying large-scale density fluctuations. This source of uncertainty can be significant, especially for surveys which cover only small areas and for massive high-redshift galaxies. Cosmic variance for a given galaxy population can be determined using predictions from cold dark matter theory and the galaxy bias. In this paper, we provide tools for experiment design and interpretation. For a given survey geometry, we present the cosmic variance of dark matter as a function of mean redshift z-bar and redshift bin size Δz. Using a halo occupation model to predict galaxy clustering, we derive the galaxy bias as a function of mean redshift for galaxy samples of a given stellar mass range. In the linear regime, the cosmic variance of these galaxy samples is the product of the galaxy bias and the dark matter cosmic variance. We present a simple recipe using a fitting function to compute cosmic variance as a function of the angular dimensions of the field, z-bar , Δz, and stellar mass m * . We also provide tabulated values and a software tool. The accuracy of the resulting cosmic variance estimates (δσ v /σ v ) is shown to be better than 20%. We find that for GOODS at z-bar =2 and with Δz = 0.5, the relative cosmic variance of galaxies with m * >10 11 M sun is ∼38%, while it is ∼27% for GEMS and ∼12% for COSMOS. For galaxies of m * ∼ 10 10 M sun , the relative cosmic variance is ∼19% for GOODS, ∼13% for GEMS, and ∼6% for COSMOS. This implies that cosmic variance is a significant source of uncertainty at z-bar =2 for small fields and massive galaxies, while for larger fields and intermediate mass galaxies, cosmic

MCNP variance reduction overview

International Nuclear Information System (INIS)

Hendricks, J.S.; Booth, T.E.

1985-01-01

The MCNP code is rich in variance reduction features. Standard variance reduction methods found in most Monte Carlo codes are available as well as a number of methods unique to MCNP. We discuss the variance reduction features presently in MCNP as well as new ones under study for possible inclusion in future versions of the code

Spectral Ambiguity of Allan Variance

Science.gov (United States)

Greenhall, C. A.

1996-01-01

We study the extent to which knowledge of Allan variance and other finite-difference variances determines the spectrum of a random process. The variance of first differences is known to determine the spectrum. We show that, in general, the Allan variance does not. A complete description of the ambiguity is given.

Phenotypic and genotypic variability of disc flower corolla length and nectar content in sunflower

Directory of Open Access Journals (Sweden)

Joksimović Jovan

2003-01-01

Full Text Available The nectar content and disc flower corolla length are the two most important parameters of attractiveness to pollinators in sunflower. The phenotypic and genotypic variability of these two traits was studied in four commercially important hybrids and their parental components in a trial with three fertilizer doses over two years. The results showed that, looking at individual genotypes, the variability of disc flower corolla length was affected the most by year (85.38-97.46%. As the study years were extremely different, the phenotypic variance of the hybrids and parental components was calculated for each year separately. In such conditions, looking at all of the crossing combinations, the largest contribution to phenotypic variance of the corolla length was that of genotype: 57.27-61.11% (NS-H-45 64.51-84.84% (Velja; 96.74-97.20% (NS-H-702 and 13.92-73.17% (NS-H-111. A similar situation was observed for the phenotypic variability of nectar content, where genotype also had the largest influence, namely 39.77-48.25% in NS-H-45; 39.06-42.51% in Velja; 31.97-72.36% in NS-H-702; and 62.13-94.96% in NS-H-111.

Analisis Ragam dan Peragam Bobot Badan Kambing Peranakan Etawa (ANALYSIS VARIANCE AND COVARIANCE OF BODY WEIGHT OF ETTAWA GRADE GOAT

Directory of Open Access Journals (Sweden)

Siti Hidayati

2015-05-01

Full Text Available The aims of this study were (1 to analyze the phenotypic performance of Ettawa Grade (EG goat; (2to estimate the heritability of birth weight (BW, weaning weight (WW, yearling weight (YW, and geneticcorrelation between two body weights on the third different period; and (3 to analyze the variance andcovariance component of body weight. The material used were the exiting records of 437 EG goats in BalaiPembibitan Ternak Unggul dan Hijauan Pakan Ternak Pelaihari, South Kalimantan. These goats originatedfrom the crossing between 19 males and 216 females from periods of 2009 - 2012. Nested Design methodwas used to etimate the phenotypic correlation, heritability and genetic correlation. Variance componentswere determined from heritability estimation, while covariance components were determined from geneticcerrelation estimation. Phenotypic correlation between BW and WW, between BW and YW, and betweenWW and YW were 0.19 (low; 0.31 (medium; 0.65 (high; respectively. Heritability of BW, WW, and YW were0.43±0.23 (high; WW 0.27±0.19 (medium; and YW 1.01±0.38 (excludeof the h2 value, respectively.Genetic correlation between BW and WW, between BW and YW, and between WW and YW were -0.04(negative low; 0.49 (positive medium; and -0.41 (negative medium, respectively. Variance components ofbuck, ewes, and kid for BW were 10.76%; 37.16%; and 52.09%, respectively, for WW were 6.67%; 38.52%;and 54.81%, respectively, and for YW were 25.15%; 58.37%; and 16.43%, respectively. Covariancecomponents of buck, ewes, and kid between BW and WW were -3.91%; 66.45%; and 37.46%, respectively,between BW and YW were 65.68%; 16.50%; and 17.82, and between WW and YW were -5.14%; 83.87%; and21.28%, respectively. In conclusions variance component of ewes and kid were high in body weight at birthand weaning time. Therefore, selection should be conducted for body weight at birth and weaning time.

The macroevolutionary consequences of phenotypic integration: from development to deep time.

Science.gov (United States)

Goswami, A; Smaers, J B; Soligo, C; Polly, P D

2014-08-19

Phenotypic integration is a pervasive characteristic of organisms. Numerous analyses have demonstrated that patterns of phenotypic integration are conserved across large clades, but that significant variation also exists. For example, heterochronic shifts related to different mammalian reproductive strategies are reflected in postcranial skeletal integration and in coordination of bone ossification. Phenotypic integration and modularity have been hypothesized to shape morphological evolution, and we extended simulations to confirm that trait integration can influence both the trajectory and magnitude of response to selection. We further demonstrate that phenotypic integration can produce both more and less disparate organisms than would be expected under random walk models by repartitioning variance in preferred directions. This effect can also be expected to favour homoplasy and convergent evolution. New empirical analyses of the carnivoran cranium show that rates of evolution, in contrast, are not strongly influenced by phenotypic integration and show little relationship to morphological disparity, suggesting that phenotypic integration may shape the direction of evolutionary change, but not necessarily the speed of it. Nonetheless, phenotypic integration is problematic for morphological clocks and should be incorporated more widely into models that seek to accurately reconstruct both trait and organismal evolution.

Adaptation to an extraordinary environment by evolution of phenotypic plasticity and genetic assimilation.

Science.gov (United States)

Lande, Russell

2009-07-01

Adaptation to a sudden extreme change in environment, beyond the usual range of background environmental fluctuations, is analysed using a quantitative genetic model of phenotypic plasticity. Generations are discrete, with time lag tau between a critical period for environmental influence on individual development and natural selection on adult phenotypes. The optimum phenotype, and genotypic norms of reaction, are linear functions of the environment. Reaction norm elevation and slope (plasticity) vary among genotypes. Initially, in the average background environment, the character is canalized with minimum genetic and phenotypic variance, and no correlation between reaction norm elevation and slope. The optimal plasticity is proportional to the predictability of environmental fluctuations over time lag tau. During the first generation in the new environment the mean fitness suddenly drops and the mean phenotype jumps towards the new optimum phenotype by plasticity. Subsequent adaptation occurs in two phases. Rapid evolution of increased plasticity allows the mean phenotype to closely approach the new optimum. The new phenotype then undergoes slow genetic assimilation, with reduction in plasticity compensated by genetic evolution of reaction norm elevation in the original environment.

VARIANCE COMPONENTS AND SELECTION FOR FEATHER PECKING BEHAVIOR IN LAYING HENS

OpenAIRE

Su, Guosheng; Kjaer, Jørgen B.; Sørensen, Poul

2005-01-01

Variance components and selection response for feather pecking behaviour were studied by analysing the data from a divergent selection experiment. An investigation show that a Box-Cox transformation with power =-0.2 made the data be approximately normally distributed and fit best by the given model. Variance components and selection response were estimated using Bayesian analysis with Gibbs sampling technique. The total variation was rather large for the two traits in both low feather peckin...

Does degree of gyrification underlie the phenotypic and genetic associations between cortical surface area and cognitive ability?

Science.gov (United States)

Docherty, Anna R; Hagler, Donald J; Panizzon, Matthew S; Neale, Michael C; Eyler, Lisa T; Fennema-Notestine, Christine; Franz, Carol E; Jak, Amy; Lyons, Michael J; Rinker, Daniel A; Thompson, Wesley K; Tsuang, Ming T; Dale, Anders M; Kremen, William S

2015-02-01

The phenotypic and genetic relationship between global cortical size and general cognitive ability (GCA) appears to be driven by surface area (SA) and not cortical thickness (CT). Gyrification (cortical folding) is an important property of the cortex that helps to increase SA within a finite space, and may also improve connectivity by reducing distance between regions. Hence, gyrification may be what underlies the SA-GCA relationship. In previous phenotypic studies, a 3-dimensional gyrification index (3DGI) has been positively associated with cognitive ability and negatively associated with mild cognitive impairment, Alzheimer's disease, and psychiatric disorders affecting cognition. However, the differential genetic associations of 3DGI and SA with GCA are still unclear. We examined the heritability of 3DGI, and the phenotypic, genetic, and environmental associations of 3DGI with SA and GCA in a large sample of adult male twins (N = 512). Nearly 85% of the variance in 3DGI was due to genes, and 3DGI had a strong phenotypic and genetic association with SA. Both 3DGI and total SA had positive phenotypic correlations with GCA. However, the SA-GCA correlation remained significant after controlling for 3DGI, but not the other way around. There was also significant genetic covariance between SA and GCA, but not between 3DGI and GCA. Thus, despite the phenotypic and genetic associations between 3DGI and SA, our results do not support the hypothesis that gyrification underlies the association between SA and GCA. Copyright © 2014 Elsevier Inc. All rights reserved.

An elementary components of variance analysis for multi-center quality control

International Nuclear Information System (INIS)

Munson, P.J.; Rodbard, D.

1977-01-01

The serious variability of RIA results from different laboratories indicates the need for multi-laboratory collaborative quality control (QC) studies. Statistical analysis methods for such studies using an 'analysis of variance with components of variance estimation' are discussed. This technique allocates the total variance into components corresponding to between-laboratory, between-assay, and residual or within-assay variability. Components of variance analysis also provides an intelligent way to combine the results of several QC samples run at different evels, from which we may decide if any component varies systematically with dose level; if not, pooling of estimates becomes possible. We consider several possible relationships of standard deviation to the laboratory mean. Each relationship corresponds to an underlying statistical model, and an appropriate analysis technique. Tests for homogeneity of variance may be used to determine if an appropriate model has been chosen, although the exact functional relationship of standard deviation to lab mean may be difficult to establish. Appropriate graphical display of the data aids in visual understanding of the data. A plot of the ranked standard deviation vs. ranked laboratory mean is a convenient way to summarize a QC study. This plot also allows determination of the rank correlation, which indicates a net relationship of variance to laboratory mean. (orig.) [de

Molecular variance of the Tunisian almond germplasm assessed by ...

African Journals Online (AJOL)

The genetic variance analysis of 82 almond (Prunus dulcis Mill.) genotypes was performed using ten genomic simple sequence repeats (SSRs). A total of 50 genotypes from Tunisia including local landraces identified while prospecting the different sites of Bizerte and Sidi Bouzid (Northern and central parts) which are the ...

How does variance in fertility change over the demographic transition?

Science.gov (United States)

Hruschka, Daniel J; Burger, Oskar

2016-04-19

Most work on the human fertility transition has focused on declines in mean fertility. However, understanding changes in the variance of reproductive outcomes can be equally important for evolutionary questions about the heritability of fertility, individual determinants of fertility and changing patterns of reproductive skew. Here, we document how variance in completed fertility among women (45-49 years) differs across 200 surveys in 72 low- to middle-income countries where fertility transitions are currently in progress at various stages. Nearly all (91%) of samples exhibit variance consistent with a Poisson process of fertility, which places systematic, and often severe, theoretical upper bounds on the proportion of variance that can be attributed to individual differences. In contrast to the pattern of total variance, these upper bounds increase from high- to mid-fertility samples, then decline again as samples move from mid to low fertility. Notably, the lowest fertility samples often deviate from a Poisson process. This suggests that as populations move to low fertility their reproduction shifts from a rate-based process to a focus on an ideal number of children. We discuss the implications of these findings for predicting completed fertility from individual-level variables. © 2016 The Author(s).

Reexamining financial and economic predictability with new estimators of realized variance and variance risk premium

DEFF Research Database (Denmark)

Casas, Isabel; Mao, Xiuping; Veiga, Helena

This study explores the predictive power of new estimators of the equity variance risk premium and conditional variance for future excess stock market returns, economic activity, and financial instability, both during and after the last global financial crisis. These estimators are obtained from...... time-varying coefficient models are the ones showing considerably higher predictive power for stock market returns and financial instability during the financial crisis, suggesting that an extreme volatility period requires models that can adapt quickly to turmoil........ Moreover, a comparison of the overall results reveals that the conditional variance gains predictive power during the global financial crisis period. Furthermore, both the variance risk premium and conditional variance are determined to be predictors of future financial instability, whereas conditional...

Quantitative genetic variance and multivariate clines in the Ivyleaf morning glory, Ipomoea hederacea.

Science.gov (United States)

Stock, Amanda J; Campitelli, Brandon E; Stinchcombe, John R

2014-08-19

Clinal variation is commonly interpreted as evidence of adaptive differentiation, although clines can also be produced by stochastic forces. Understanding whether clines are adaptive therefore requires comparing clinal variation to background patterns of genetic differentiation at presumably neutral markers. Although this approach has frequently been applied to single traits at a time, we have comparatively fewer examples of how multiple correlated traits vary clinally. Here, we characterize multivariate clines in the Ivyleaf morning glory, examining how suites of traits vary with latitude, with the goal of testing for divergence in trait means that would indicate past evolutionary responses. We couple this with analysis of genetic variance in clinally varying traits in 20 populations to test whether past evolutionary responses have depleted genetic variance, or whether genetic variance declines approaching the range margin. We find evidence of clinal differentiation in five quantitative traits, with little evidence of isolation by distance at neutral loci that would suggest non-adaptive or stochastic mechanisms. Within and across populations, the traits that contribute most to population differentiation and clinal trends in the multivariate phenotype are genetically variable as well, suggesting that a lack of genetic variance will not cause absolute evolutionary constraints. Our data are broadly consistent theoretical predictions of polygenic clines in response to shallow environmental gradients. Ecologically, our results are consistent with past findings of natural selection on flowering phenology, presumably due to season-length variation across the range. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Building bridges across electronic health record systems through inferred phenotypic topics.

Science.gov (United States)

Chen, You; Ghosh, Joydeep; Bejan, Cosmin Adrian; Gunter, Carl A; Gupta, Siddharth; Kho, Abel; Liebovitz, David; Sun, Jimeng; Denny, Joshua; Malin, Bradley

2015-06-01

Data in electronic health records (EHRs) is being increasingly leveraged for secondary uses, ranging from biomedical association studies to comparative effectiveness. To perform studies at scale and transfer knowledge from one institution to another in a meaningful way, we need to harmonize the phenotypes in such systems. Traditionally, this has been accomplished through expert specification of phenotypes via standardized terminologies, such as billing codes. However, this approach may be biased by the experience and expectations of the experts, as well as the vocabulary used to describe such patients. The goal of this work is to develop a data-driven strategy to (1) infer phenotypic topics within patient populations and (2) assess the degree to which such topics facilitate a mapping across populations in disparate healthcare systems. We adapt a generative topic modeling strategy, based on latent Dirichlet allocation, to infer phenotypic topics. We utilize a variance analysis to assess the projection of a patient population from one healthcare system onto the topics learned from another system. The consistency of learned phenotypic topics was evaluated using (1) the similarity of topics, (2) the stability of a patient population across topics, and (3) the transferability of a topic across sites. We evaluated our approaches using four months of inpatient data from two geographically distinct healthcare systems: (1) Northwestern Memorial Hospital (NMH) and (2) Vanderbilt University Medical Center (VUMC). The method learned 25 phenotypic topics from each healthcare system. The average cosine similarity between matched topics across the two sites was 0.39, a remarkably high value given the very high dimensionality of the feature space. The average stability of VUMC and NMH patients across the topics of two sites was 0.988 and 0.812, respectively, as measured by the Pearson correlation coefficient. Also the VUMC and NMH topics have smaller variance of characterizing

Phenotypic Plasticity of Leaf Shape along a Temperature Gradient in Acer rubrum

Science.gov (United States)

Royer, Dana L.; Meyerson, Laura A.; Robertson, Kevin M.; Adams, Jonathan M.

2009-01-01

Both phenotypic plasticity and genetic determination can be important for understanding how plants respond to environmental change. However, little is known about the plastic response of leaf teeth and leaf dissection to temperature. This gap is critical because these leaf traits are commonly used to reconstruct paleoclimate from fossils, and such studies tacitly assume that traits measured from fossils reflect the environment at the time of their deposition, even during periods of rapid climate change. We measured leaf size and shape in Acer rubrum derived from four seed sources with a broad temperature range and grown for two years in two gardens with contrasting climates (Rhode Island and Florida). Leaves in the Rhode Island garden have more teeth and are more highly dissected than leaves in Florida from the same seed source. Plasticity in these variables accounts for at least 6–19 % of the total variance, while genetic differences among ecotypes probably account for at most 69–87 %. This study highlights the role of phenotypic plasticity in leaf-climate relationships. We suggest that variables related to tooth count and leaf dissection in A. rubrum can respond quickly to climate change, which increases confidence in paleoclimate methods that use these variables. PMID:19893620

A zero-variance-based scheme for variance reduction in Monte Carlo criticality

Energy Technology Data Exchange (ETDEWEB)

Christoforou, S.; Hoogenboom, J. E. [Delft Univ. of Technology, Mekelweg 15, 2629 JB Delft (Netherlands)

2006-07-01

A zero-variance scheme is derived and proven theoretically for criticality cases, and a simplified transport model is used for numerical demonstration. It is shown in practice that by appropriate biasing of the transition and collision kernels, a significant reduction in variance can be achieved. This is done using the adjoint forms of the emission and collision densities, obtained from a deterministic calculation, according to the zero-variance scheme. By using an appropriate algorithm, the figure of merit of the simulation increases by up to a factor of 50, with the possibility of an even larger improvement. In addition, it is shown that the biasing speeds up the convergence of the initial source distribution. (authors)

A zero-variance-based scheme for variance reduction in Monte Carlo criticality

International Nuclear Information System (INIS)

Christoforou, S.; Hoogenboom, J. E.

2006-01-01

A zero-variance scheme is derived and proven theoretically for criticality cases, and a simplified transport model is used for numerical demonstration. It is shown in practice that by appropriate biasing of the transition and collision kernels, a significant reduction in variance can be achieved. This is done using the adjoint forms of the emission and collision densities, obtained from a deterministic calculation, according to the zero-variance scheme. By using an appropriate algorithm, the figure of merit of the simulation increases by up to a factor of 50, with the possibility of an even larger improvement. In addition, it is shown that the biasing speeds up the convergence of the initial source distribution. (authors)

Genetic Regulation of Phenotypic Plasticity and Canalisation in Yeast Growth.

Directory of Open Access Journals (Sweden)

Anupama Yadav

Full Text Available The ability of a genotype to show diverse phenotypes in different environments is called phenotypic plasticity. Phenotypic plasticity helps populations to evade extinctions in novel environments, facilitates adaptation and fuels evolution. However, most studies focus on understanding the genetic basis of phenotypic regulation in specific environments. As a result, while it's evolutionary relevance is well established, genetic mechanisms regulating phenotypic plasticity and their overlap with the environment specific regulators is not well understood. Saccharomyces cerevisiae is highly sensitive to the environment, which acts as not just external stimulus but also as signalling cue for this unicellular, sessile organism. We used a previously published dataset of a biparental yeast population grown in 34 diverse environments and mapped genetic loci regulating variation in phenotypic plasticity, plasticity QTL, and compared them with environment-specific QTL. Plasticity QTL is one whose one allele exhibits high plasticity whereas the other shows a relatively canalised behaviour. We mapped phenotypic plasticity using two parameters-environmental variance, an environmental order-independent parameter and reaction norm (slope, an environmental order-dependent parameter. Our results show a partial overlap between pleiotropic QTL and plasticity QTL such that while some plasticity QTL are also pleiotropic, others have a significant effect on phenotypic plasticity without being significant in any environment independently. Furthermore, while some plasticity QTL are revealed only in specific environmental orders, we identify large effect plasticity QTL, which are order-independent such that whatever the order of the environments, one allele is always plastic and the other is canalised. Finally, we show that the environments can be divided into two categories based on the phenotypic diversity of the population within them and the two categories have

Genetic and phenotypic variance and covariance components for methane emission and postweaning traits in Angus cattle.

Science.gov (United States)

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

An elementary components of variance analysis for multi-centre quality control

International Nuclear Information System (INIS)

Munson, P.J.; Rodbard, D.

1978-01-01

The serious variability of RIA results from different laboratories indicates the need for multi-laboratory collaborative quality-control (QC) studies. Simple graphical display of data in the form of histograms is useful but insufficient. The paper discusses statistical analysis methods for such studies using an ''analysis of variance with components of variance estimation''. This technique allocates the total variance into components corresponding to between-laboratory, between-assay, and residual or within-assay variability. Problems with RIA data, e.g. severe non-uniformity of variance and/or departure from a normal distribution violate some of the usual assumptions underlying analysis of variance. In order to correct these problems, it is often necessary to transform the data before analysis by using a logarithmic, square-root, percentile, ranking, RIDIT, ''Studentizing'' or other transformation. Ametric transformations such as ranks or percentiles protect against the undue influence of outlying observations, but discard much intrinsic information. Several possible relationships of standard deviation to the laboratory mean are considered. Each relationship corresponds to an underlying statistical model and an appropriate analysis technique. Tests for homogeneity of variance may be used to determine whether an appropriate model has been chosen, although the exact functional relationship of standard deviation to laboratory mean may be difficult to establish. Appropriate graphical display aids visual understanding of the data. A plot of the ranked standard deviation versus ranked laboratory mean is a convenient way to summarize a QC study. This plot also allows determination of the rank correlation, which indicates a net relationship of variance to laboratory mean

Noise-Driven Phenotypic Heterogeneity with Finite Correlation Time in Clonal Populations.

Directory of Open Access Journals (Sweden)

UnJin Lee

Full Text Available There has been increasing awareness in the wider biological community of the role of clonal phenotypic heterogeneity in playing key roles in phenomena such as cellular bet-hedging and decision making, as in the case of the phage-λ lysis/lysogeny and B. Subtilis competence/vegetative pathways. Here, we report on the effect of stochasticity in growth rate, cellular memory/intermittency, and its relation to phenotypic heterogeneity. We first present a linear stochastic differential model with finite auto-correlation time, where a randomly fluctuating growth rate with a negative average is shown to result in exponential growth for sufficiently large fluctuations in growth rate. We then present a non-linear stochastic self-regulation model where the loss of coherent self-regulation and an increase in noise can induce a shift from bounded to unbounded growth. An important consequence of these models is that while the average change in phenotype may not differ for various parameter sets, the variance of the resulting distributions may considerably change. This demonstrates the necessity of understanding the influence of variance and heterogeneity within seemingly identical clonal populations, while providing a mechanism for varying functional consequences of such heterogeneity. Our results highlight the importance of a paradigm shift from a deterministic to a probabilistic view of clonality in understanding selection as an optimization problem on noise-driven processes, resulting in a wide range of biological implications, from robustness to environmental stress to the development of drug resistance.

Genetic control of residual variance of yearling weight in Nellore beef cattle.

Science.gov (United States)

Iung, L H S; Neves, H H R; Mulder, H A; Carvalheiro, R

2017-04-01

There is evidence for genetic variability in residual variance of livestock traits, which offers the potential for selection for increased uniformity of production. Different statistical approaches have been employed to study this topic; however, little is known about the concordance between them. The aim of our study was to investigate the genetic heterogeneity of residual variance on yearling weight (YW; 291.15 ± 46.67) in a Nellore beef cattle population; to compare the results of the statistical approaches, the two-step approach and the double hierarchical generalized linear model (DHGLM); and to evaluate the effectiveness of power transformation to accommodate scale differences. The comparison was based on genetic parameters, accuracy of EBV for residual variance, and cross-validation to assess predictive performance of both approaches. A total of 194,628 yearling weight records from 625 sires were used in the analysis. The results supported the hypothesis of genetic heterogeneity of residual variance on YW in Nellore beef cattle and the opportunity of selection, measured through the genetic coefficient of variation of residual variance (0.10 to 0.12 for the two-step approach and 0.17 for DHGLM, using an untransformed data set). However, low estimates of genetic variance associated with positive genetic correlations between mean and residual variance (about 0.20 for two-step and 0.76 for DHGLM for an untransformed data set) limit the genetic response to selection for uniformity of production while simultaneously increasing YW itself. Moreover, large sire families are needed to obtain accurate estimates of genetic merit for residual variance, as indicated by the low heritability estimates (Box-Cox transformation was able to decrease the dependence of the variance on the mean and decreased the estimates of genetic parameters for residual variance. The transformation reduced but did not eliminate all the genetic heterogeneity of residual variance, highlighting

Numerical simulation of variance of solar radiation and its influence on wheat growth

Science.gov (United States)

Zhang, Xuefen; Wang, Chunyi; Du, Zixuan; Zhai, Wei

2007-09-01

The growth of crops is directly related to solar radiation whose variances influence the photosynthesis of crops and the growth momentum thereof. This dissertation has Zhengzhou, which located in the Huanghuai Farmland Ecological System of China, as an example to analyze the rules of variances of total solar radiation, direct radiation and diffusive radiation. With the help of linear trend fitting, it is identified that total radiation (TR) drops as a whole at a rate of 1.6482J/m2. Such drop has been particularly apparent in recent years with a period of 7 to 16 years; diffusive radiation (DF) tends to increase at a rate of 15.149 J/m2 with a period of 20 years; direct radiation (DR) tends to drop at a rate of 15.843 J/m2 without apparent period. The total radiation has been on the decrease ever since 1980 during the growth period of wheat. Having modified relevant Parameter in the Carbon and Nitrogen Biogeochemistry in Agroecosystems Model (DNDC) model and simulated the influence of solar radiation variances on the development phase, leaf area index (LAI), grain weight, etc during the growth period of wheat, it is found that solar radiation is in positive proportion to LAI and grain weight (GRNWT) but not apparently related to development phase (DP). The change of total radiation delays the maximization of wheat LAI, reduces wheat LAI before winter but has no apparent effect in winter and decreases wheat LAI from jointing period to filling period; it has no apparent influence on grain formation at the early stage of grain formation, slows down the weight increase of grains during the filling period and accelerates the weight increase of grains at the end of filling period. Variance of radiations does not affect the DP of wheat much.

Variance in predicted cup size by 2-dimensional vs 3-dimensional computerized tomography-based templating in primary total hip arthroplasty.

Science.gov (United States)

Osmani, Feroz A; Thakkar, Savyasachi; Ramme, Austin; Elbuluk, Ameer; Wojack, Paul; Vigdorchik, Jonathan M

2017-12-01

Preoperative total hip arthroplasty templating can be performed with radiographs using acetate prints, digital viewing software, or with computed tomography (CT) images. Our hypothesis is that 3D templating is more precise and accurate with cup size prediction as compared to 2D templating with acetate prints and digital templating software. Data collected from 45 patients undergoing robotic-assisted total hip arthroplasty compared cup sizes templated on acetate prints and OrthoView software to MAKOplasty software that uses CT scan. Kappa analysis determined strength of agreement between each templating modality and the final size used. t tests compared mean cup-size variance from the final size for each templating technique. Interclass correlation coefficient (ICC) determined reliability of digital and acetate planning by comparing predictions of the operating surgeon and a blinded adult reconstructive fellow. The Kappa values for CT-guided, digital, and acetate templating with the final size was 0.974, 0.233, and 0.262, respectively. Both digital and acetate templating significantly overpredicted cup size, compared to CT-guided methods ( P cup size when compared to the significant overpredictions of digital and acetate templating. CT-guided templating may also lead to better outcomes due to bone stock preservation from a smaller and more accurate cup size predicted than that of digital and acetate predictions.

Genetic and environmental variances of bone microarchitecture and bone remodeling markers: a twin study.

Science.gov (United States)

Bjørnerem, Åshild; Bui, Minh; Wang, Xiaofang; Ghasem-Zadeh, Ali; Hopper, John L; Zebaze, Roger; Seeman, Ego

2015-03-01

All genetic and environmental factors contributing to differences in bone structure between individuals mediate their effects through the final common cellular pathway of bone modeling and remodeling. We hypothesized that genetic factors account for most of the population variance of cortical and trabecular microstructure, in particular intracortical porosity and medullary size - void volumes (porosity), which establish the internal bone surface areas or interfaces upon which modeling and remodeling deposit or remove bone to configure bone microarchitecture. Microarchitecture of the distal tibia and distal radius and remodeling markers were measured for 95 monozygotic (MZ) and 66 dizygotic (DZ) white female twin pairs aged 40 to 61 years. Images obtained using high-resolution peripheral quantitative computed tomography were analyzed using StrAx1.0, a nonthreshold-based software that quantifies cortical matrix and porosity. Genetic and environmental components of variance were estimated under the assumptions of the classic twin model. The data were consistent with the proportion of variance accounted for by genetic factors being: 72% to 81% (standard errors ∼18%) for the distal tibial total, cortical, and medullary cross-sectional area (CSA); 67% and 61% for total cortical porosity, before and after adjusting for total CSA, respectively; 51% for trabecular volumetric bone mineral density (vBMD; all p accounted for 47% to 68% of the variance (all p ≤ 0.001). Cross-twin cross-trait correlations between tibial cortical porosity and medullary CSA were higher for MZ (rMZ  = 0.49) than DZ (rDZ  = 0.27) pairs before (p = 0.024), but not after (p = 0.258), adjusting for total CSA. For the remodeling markers, the data were consistent with genetic factors accounting for 55% to 62% of the variance. We infer that middle-aged women differ in their bone microarchitecture and remodeling markers more because of differences in their genetic factors than

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.

Science.gov (United States)

Dazard, Jean-Eudes; Rao, J Sunil

2012-07-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput "omics" data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel "similarity statistic"-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called 'MVR' ('Mean-Variance Regularization'), downloadable from the CRAN website.

Portfolio optimization using median-variance approach

Science.gov (United States)

Wan Mohd, Wan Rosanisah; Mohamad, Daud; Mohamed, Zulkifli

2013-04-01

Optimization models have been applied in many decision-making problems particularly in portfolio selection. Since the introduction of Markowitz's theory of portfolio selection, various approaches based on mathematical programming have been introduced such as mean-variance, mean-absolute deviation, mean-variance-skewness and conditional value-at-risk (CVaR) mainly to maximize return and minimize risk. However most of the approaches assume that the distribution of data is normal and this is not generally true. As an alternative, in this paper, we employ the median-variance approach to improve the portfolio optimization. This approach has successfully catered both types of normal and non-normal distribution of data. With this actual representation, we analyze and compare the rate of return and risk between the mean-variance and the median-variance based portfolio which consist of 30 stocks from Bursa Malaysia. The results in this study show that the median-variance approach is capable to produce a lower risk for each return earning as compared to the mean-variance approach.

Efficient Cardinality/Mean-Variance Portfolios

OpenAIRE

Brito, R. Pedro; Vicente, Luís Nunes

2014-01-01

International audience; We propose a novel approach to handle cardinality in portfolio selection, by means of a biobjective cardinality/mean-variance problem, allowing the investor to analyze the efficient tradeoff between return-risk and number of active positions. Recent progress in multiobjective optimization without derivatives allow us to robustly compute (in-sample) the whole cardinality/mean-variance efficient frontier, for a variety of data sets and mean-variance models. Our results s...

Decomposing Additive Genetic Variance Revealed Novel Insights into Trait Evolution in Synthetic Hexaploid Wheat

Directory of Open Access Journals (Sweden)

Abdulqader Jighly

2018-02-01

Full Text Available Whole genome duplication (WGD is an evolutionary phenomenon, which causes significant changes to genomic structure and trait architecture. In recent years, a number of studies decomposed the additive genetic variance explained by different sets of variants. However, they investigated diploid populations only and none of the studies examined any polyploid organism. In this research, we extended the application of this approach to polyploids, to differentiate the additive variance explained by the three subgenomes and seven sets of homoeologous chromosomes in synthetic allohexaploid wheat (SHW to gain a better understanding of trait evolution after WGD. Our SHW population was generated by crossing improved durum parents (Triticum turgidum; 2n = 4x = 28, AABB subgenomes with the progenitor species Aegilops tauschii (syn Ae. squarrosa, T. tauschii; 2n = 2x = 14, DD subgenome. The population was phenotyped for 10 fungal/nematode resistance traits as well as two abiotic stresses. We showed that the wild D subgenome dominated the additive effect and this dominance affected the A more than the B subgenome. We provide evidence that this dominance was not inflated by population structure, relatedness among individuals or by longer linkage disequilibrium blocks observed in the D subgenome within the population used for this study. The cumulative size of the three homoeologs of the seven chromosomal groups showed a weak but significant positive correlation with their cumulative explained additive variance. Furthermore, an average of 69% for each chromosomal group's cumulative additive variance came from one homoeolog that had the highest explained variance within the group across all 12 traits. We hypothesize that structural and functional changes during diploidization may explain chromosomal group relations as allopolyploids keep balanced dosage for many genes. Our results contribute to a better understanding of trait evolution mechanisms in polyploidy

Robust LOD scores for variance component-based linkage analysis.

Science.gov (United States)

Blangero, J; Williams, J T; Almasy, L

2000-01-01

The variance component method is now widely used for linkage analysis of quantitative traits. Although this approach offers many advantages, the importance of the underlying assumption of multivariate normality of the trait distribution within pedigrees has not been studied extensively. Simulation studies have shown that traits with leptokurtic distributions yield linkage test statistics that exhibit excessive Type I error when analyzed naively. We derive analytical formulae relating the deviation from the expected asymptotic distribution of the lod score to the kurtosis and total heritability of the quantitative trait. A simple correction constant yields a robust lod score for any deviation from normality and for any pedigree structure, and effectively eliminates the problem of inflated Type I error due to misspecification of the underlying probability model in variance component-based linkage analysis.

Variance Component Selection With Applications to Microbiome Taxonomic Data

Directory of Open Access Journals (Sweden)

Jing Zhai

2018-03-01

Full Text Available High-throughput sequencing technology has enabled population-based studies of the role of the human microbiome in disease etiology and exposure response. Microbiome data are summarized as counts or composition of the bacterial taxa at different taxonomic levels. An important problem is to identify the bacterial taxa that are associated with a response. One method is to test the association of specific taxon with phenotypes in a linear mixed effect model, which incorporates phylogenetic information among bacterial communities. Another type of approaches consider all taxa in a joint model and achieves selection via penalization method, which ignores phylogenetic information. In this paper, we consider regression analysis by treating bacterial taxa at different level as multiple random effects. For each taxon, a kernel matrix is calculated based on distance measures in the phylogenetic tree and acts as one variance component in the joint model. Then taxonomic selection is achieved by the lasso (least absolute shrinkage and selection operator penalty on variance components. Our method integrates biological information into the variable selection problem and greatly improves selection accuracies. Simulation studies demonstrate the superiority of our methods versus existing methods, for example, group-lasso. Finally, we apply our method to a longitudinal microbiome study of Human Immunodeficiency Virus (HIV infected patients. We implement our method using the high performance computing language Julia. Software and detailed documentation are freely available at https://github.com/JingZhai63/VCselection.

Approximation errors during variance propagation

International Nuclear Information System (INIS)

Dinsmore, Stephen

1986-01-01

Risk and reliability analyses are often performed by constructing and quantifying large fault trees. The inputs to these models are component failure events whose probability of occuring are best represented as random variables. This paper examines the errors inherent in two approximation techniques used to calculate the top event's variance from the inputs' variance. Two sample fault trees are evaluated and several three dimensional plots illustrating the magnitude of the error over a wide range of input means and variances are given

Phenotype diversity analysis of red-grained rice landraces from Yuanyang Hani's terraced fields, China

Science.gov (United States)

Li, Lianjie; Cheng, Long

2017-10-01

There are many areas in the world have terraced fields, Yuanyang Rani's terraced fields are examples in the world, and their unique ecological diversity is beyond other terraced fields, rice landraces are very rich. In order to provide useful information for protection and utilization of red-grained rice landraces from Rani's terraced fields, 61 red-grained rice landraces were assessed based 20 quantitative traits. Principal component analysis (PCA) suggested that 20 quantitative characters could be simplified to seven principal components, and their accumulative contribution ration amounted to 78.699%. The first principal component (PC1) explained 18.375% of the total variance, which was contributed by filled grain number, 1000-grain weight, spikelets per panicle, secondary branch number, grain length, and grain thickness. PC2 accounted for 16.548% of the variance and featured flag leaf width, flag leaf area, panicle neck length and primary branch number. These traits were the most effective parameters to discriminate individuals. At the request of the proceedings editor and with the approval of all authors, article 040111 titled, "Phenotype diversity analysis of red-grained rice landraces from Yuanyang Hani's terraced fields, China," is being retracted from the public record due to the fact that it is a duplication of article 040110 published in the same volume.

Genetic variation in variability: phenotypic variability of fledging weight and its evolution in a songbird population

NARCIS (Netherlands)

Mulder, H.A.; Gienapp, P; Visser, ME

2016-01-01

Variation in traits is essential for natural selection to operate and genetic and environmental effects can contribute to this phenotypic variation. From domesticated populations, we know that families can differ in their level of within-family variance, which leads to the intriguing situation that

A new interpretation and validation of variance based importance measures for models with correlated inputs

Science.gov (United States)

Hao, Wenrui; Lu, Zhenzhou; Li, Luyi

2013-05-01

In order to explore the contributions by correlated input variables to the variance of the output, a novel interpretation framework of importance measure indices is proposed for a model with correlated inputs, which includes the indices of the total correlated contribution and the total uncorrelated contribution. The proposed indices accurately describe the connotations of the contributions by the correlated input to the variance of output, and they can be viewed as the complement and correction of the interpretation about the contributions by the correlated inputs presented in "Estimation of global sensitivity indices for models with dependent variables, Computer Physics Communications, 183 (2012) 937-946". Both of them contain the independent contribution by an individual input. Taking the general form of quadratic polynomial as an illustration, the total correlated contribution and the independent contribution by an individual input are derived analytically, from which the components and their origins of both contributions of correlated input can be clarified without any ambiguity. In the special case that no square term is included in the quadratic polynomial model, the total correlated contribution by the input can be further decomposed into the variance contribution related to the correlation of the input with other inputs and the independent contribution by the input itself, and the total uncorrelated contribution can be further decomposed into the independent part by interaction between the input and others and the independent part by the input itself. Numerical examples are employed and their results demonstrate that the derived analytical expressions of the variance-based importance measure are correct, and the clarification of the correlated input contribution to model output by the analytical derivation is very important for expanding the theory and solutions of uncorrelated input to those of the correlated one.

Estimation of the additive and dominance variances in South African ...

African Journals Online (AJOL)

The objective of this study was to estimate dominance variance for number born alive (NBA), 21- day litter weight (LWT21) and interval between parities (FI) in South African Landrace pigs. A total of 26223 NBA, 21335 LWT21 and 16370 FI records were analysed. Bayesian analysis via Gibbs sampling was used to estimate ...

The genetic variance but not the genetic covariance of life-history traits changes towards the north in a time-constrained insect.

Science.gov (United States)

Sniegula, Szymon; Golab, Maria J; Drobniak, Szymon M; Johansson, Frank

2018-03-22

Seasonal time constraints are usually stronger at higher than lower latitudes and can exert strong selection on life-history traits and the correlations among these traits. To predict the response of life-history traits to environmental change along a latitudinal gradient, information must be obtained about genetic variance in traits and also genetic correlation between traits, that is the genetic variance-covariance matrix, G. Here, we estimated G for key life-history traits in an obligate univoltine damselfly that faces seasonal time constraints. We exposed populations to simulated native temperatures and photoperiods and common garden environmental conditions in a laboratory set-up. Despite differences in genetic variance in these traits between populations (lower variance at northern latitudes), there was no evidence for latitude-specific covariance of the life-history traits. At simulated native conditions, all populations showed strong genetic and phenotypic correlations between traits that shaped growth and development. The variance-covariance matrix changed considerably when populations were exposed to common garden conditions compared with the simulated natural conditions, showing the importance of environmentally induced changes in multivariate genetic structure. Our results highlight the importance of estimating variance-covariance matrixes in environments that mimic selection pressures and not only trait variances or mean trait values in common garden conditions for understanding the trait evolution across populations and environments. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Estimation of noise-free variance to measure heterogeneity.

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Tilo Winkler

Full Text Available Variance is a statistical parameter used to characterize heterogeneity or variability in data sets. However, measurements commonly include noise, as random errors superimposed to the actual value, which may substantially increase the variance compared to a noise-free data set. Our aim was to develop and validate a method to estimate noise-free spatial heterogeneity of pulmonary perfusion using dynamic positron emission tomography (PET scans. On theoretical grounds, we demonstrate a linear relationship between the total variance of a data set derived from averages of n multiple measurements, and the reciprocal of n. Using multiple measurements with varying n yields estimates of the linear relationship including the noise-free variance as the constant parameter. In PET images, n is proportional to the number of registered decay events, and the variance of the image is typically normalized by the square of its mean value yielding a coefficient of variation squared (CV(2. The method was evaluated with a Jaszczak phantom as reference spatial heterogeneity (CV(r(2 for comparison with our estimate of noise-free or 'true' heterogeneity (CV(t(2. We found that CV(t(2 was only 5.4% higher than CV(r2. Additional evaluations were conducted on 38 PET scans of pulmonary perfusion using (13NN-saline injection. The mean CV(t(2 was 0.10 (range: 0.03-0.30, while the mean CV(2 including noise was 0.24 (range: 0.10-0.59. CV(t(2 was in average 41.5% of the CV(2 measured including noise (range: 17.8-71.2%. The reproducibility of CV(t(2 was evaluated using three repeated PET scans from five subjects. Individual CV(t(2 were within 16% of each subject's mean and paired t-tests revealed no difference among the results from the three consecutive PET scans. In conclusion, our method provides reliable noise-free estimates of CV(t(2 in PET scans, and may be useful for similar statistical problems in experimental data.

Confidence Interval Approximation For Treatment Variance In ...

African Journals Online (AJOL)

In a random effects model with a single factor, variation is partitioned into two as residual error variance and treatment variance. While a confidence interval can be imposed on the residual error variance, it is not possible to construct an exact confidence interval for the treatment variance. This is because the treatment ...

Phenotype adaptability and stability of sugarcane genotypes in the sugarcane belt of the state of Pernambuco, Brazil.

Science.gov (United States)

Dutra Filho, J A; Junior, T C; Simões Neto, D E

2014-08-29

We assessed the agroindustrial performance of 25 sugarcane genotypes adapted to the edaphoclimatic conditions of the State of Pernambuco, Brazil, within the microregions Mata Norte, Mata Sul, Região Central, Litoral Norte, and Litoral Sul. The variables analyzed were POL tonnage per hectare, sugarcane tonnage per hectare, fiber and total recoverable sugar tonnage per hectare, using a randomized block design with four repetitions. Combined variance of experiments, genetic parameter estimates, decomposition of the genotype-environment interaction, and environment stratification were analyzed. Phenotype adaptability and stability were also analyzed. The various genotypes presented great potential for improvement and a similar response pattern to the microregions Centro and Mata Sul of the state of Pernambuco. Genotypes RB863129, RB867515, RB92579, RB953180, SP81-3250, RB75126, and RB942520 were better in productivity and phenotype adaptability and stability compared to genotypes RB892700, RB943365, SP79-1011, Q138, RB943538, SP78-4764, RB953281, RB943066, RB928064, RB93509, RB72454, RB952675, RB952991, RB943161, RB942898, RB872552, RB952900, and RB942849. These genotypes are recommended as cultivation options in the sugarcane belt in the state of Pernambuco, since they stand out in terms of phenotype adaptability and stability as evaluated using the method by Annicchiarico, Lin and Bins, and the method by Eberhart and Russel.

Estimating Heritability from Nuclear Family and Pedigree Data.

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Bochud, Murielle

2017-01-01

Heritability is a measure of familial resemblance. Estimating the heritability of a trait could be one of the first steps in the gene mapping process. This chapter describes how to estimate heritability for quantitative traits from nuclear and pedigree data using the ASSOC program in the Statistical Analysis in Genetic Epidemiology (S.A.G.E.) software package. Estimating heritability rests on the assumption that the total phenotypic variance of a quantitative trait can be partitioned into independent genetic and environmental components. In turn, the genetic variance can be divided into an additive (polygenic) genetic variance, a dominance variance (nonlinear interaction effects between alleles at the same locus) and an epistatic variance (interaction effects between alleles at different loci). The last two are often assumed to be zero. The additive genetic variance represents the average effects of individual alleles on the phenotype and reflects transmissible resemblance between relatives. Heritability in the narrow sense (h 2 ) refers to the ratio of the additive genetic variance to the total phenotypic variance. Heritability is a dimensionless population-specific parameter. ASSOC estimates association parameters (regression coefficients) and variance components from family data. ASSOC uses a linear regression model in which the total residual variance is partitioned, after regressing on covariates, into the sum of random components such as an additive polygenic component, a random sibship component, random nuclear family components, a random marital component, and an individual-specific random component. Assortative mating, nonrandom ascertainment of families, and failure to account for key confounding factors may bias heritability estimates.

Genotype to phenotype mapping and the fitness landscape of the E. coli lac promoter.

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Jakub Otwinowski

Full Text Available Genotype-to-phenotype maps and the related fitness landscapes that include epistatic interactions are difficult to measure because of their high dimensional structure. Here we construct such a map using the recently collected corpora of high-throughput sequence data from the 75 base pairs long mutagenized E. coli lac promoter region, where each sequence is associated with its phenotype, the induced transcriptional activity measured by a fluorescent reporter. We find that the additive (non-epistatic contributions of individual mutations account for about two-thirds of the explainable phenotype variance, while pairwise epistasis explains about 7% of the variance for the full mutagenized sequence and about 15% for the subsequence associated with protein binding sites. Surprisingly, there is no evidence for third order epistatic contributions, and our inferred fitness landscape is essentially single peaked, with a small amount of antagonistic epistasis. There is a significant selective pressure on the wild type, which we deduce to be multi-objective optimal for gene expression in environments with different nutrient sources. We identify transcription factor (CRP and RNA polymerase binding sites in the promotor region and their interactions without difficult optimization steps. In particular, we observe evidence for previously unexplored genetic regulatory mechanisms, possibly kinetic in nature. We conclude with a cautionary note that inferred properties of fitness landscapes may be severely influenced by biases in the sequence data.

The fossil record of phenotypic integration and modularity: A deep-time perspective on developmental and evolutionary dynamics.

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Goswami, Anjali; Binder, Wendy J; Meachen, Julie; O'Keefe, F Robin

2015-04-21

Variation is the raw material for natural selection, but the factors shaping variation are still poorly understood. Genetic and developmental interactions can direct variation, but there has been little synthesis of these effects with the extrinsic factors that can shape biodiversity over large scales. The study of phenotypic integration and modularity has the capacity to unify these aspects of evolutionary study by estimating genetic and developmental interactions through the quantitative analysis of morphology, allowing for combined assessment of intrinsic and extrinsic effects. Data from the fossil record in particular are central to our understanding of phenotypic integration and modularity because they provide the only information on deep-time developmental and evolutionary dynamics, including trends in trait relationships and their role in shaping organismal diversity. Here, we demonstrate the important perspective on phenotypic integration provided by the fossil record with a study of Smilodon fatalis (saber-toothed cats) and Canis dirus (dire wolves). We quantified temporal trends in size, variance, phenotypic integration, and direct developmental integration (fluctuating asymmetry) through 27,000 y of Late Pleistocene climate change. Both S. fatalis and C. dirus showed a gradual decrease in magnitude of phenotypic integration and an increase in variance and the correlation between fluctuating asymmetry and overall integration through time, suggesting that developmental integration mediated morphological response to environmental change in the later populations of these species. These results are consistent with experimental studies and represent, to our knowledge, the first deep-time validation of the importance of developmental integration in stabilizing morphological evolution through periods of environmental change.

Portfolio optimization with mean-variance model

Science.gov (United States)

Hoe, Lam Weng; Siew, Lam Weng

2016-06-01

Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.

Landscape patterns of phenotypic variation and population structuring in a selfing grass, Elymus glaucus (blue wildrye).

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Vicky J. Erickson; Nancy L. Mandel; Frank C. Sorensen

2004-01-01

Source-related phenotypic variance was investigated in a common garden study of populations of Elymus glaucus Buckley (blue wildrye) from the Blue Mountain Ecological Province of northeastern Oregon and adjoining Washington. The primary objective of this study was to assess geographic patterns of potentially adaptive differentiation in this self-...

Digital Biomass Accumulation Using High-Throughput Plant Phenotype Data Analysis.

Science.gov (United States)

Rahaman, Md Matiur; Ahsan, Md Asif; Gillani, Zeeshan; Chen, Ming

2017-09-01

Biomass is an important phenotypic trait in functional ecology and growth analysis. The typical methods for measuring biomass are destructive, and they require numerous individuals to be cultivated for repeated measurements. With the advent of image-based high-throughput plant phenotyping facilities, non-destructive biomass measuring methods have attempted to overcome this problem. Thus, the estimation of plant biomass of individual plants from their digital images is becoming more important. In this paper, we propose an approach to biomass estimation based on image derived phenotypic traits. Several image-based biomass studies state that the estimation of plant biomass is only a linear function of the projected plant area in images. However, we modeled the plant volume as a function of plant area, plant compactness, and plant age to generalize the linear biomass model. The obtained results confirm the proposed model and can explain most of the observed variance during image-derived biomass estimation. Moreover, a small difference was observed between actual and estimated digital biomass, which indicates that our proposed approach can be used to estimate digital biomass accurately.

Adaptive increase in force variance during fatigue in tasks with low redundancy.

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Singh, Tarkeshwar; S K M, Varadhan; Zatsiorsky, Vladimir M; Latash, Mark L

2010-11-26

We tested a hypothesis that fatigue of an element (a finger) leads to an adaptive neural strategy that involves an increase in force variability in the other finger(s) and an increase in co-variation of commands to fingers to keep total force variability relatively unchanged. We tested this hypothesis using a system with small redundancy (two fingers) and a marginally redundant system (with an additional constraint related to the total moment of force produced by the fingers, unstable condition). The subjects performed isometric accurate rhythmic force production tasks by the index (I) finger and two fingers (I and middle, M) pressing together before and after a fatiguing exercise by the I finger. Fatigue led to a large increase in force variance in the I-finger task and a smaller increase in the IM-task. We quantified two components of variance in the space of hypothetical commands to fingers, finger modes. Under both stable and unstable conditions, there was a large increase in the variance component that did not affect total force and a much smaller increase in the component that did. This resulted in an increase in an index of the force-stabilizing synergy. These results indicate that marginal redundancy is sufficient to allow the central nervous system to use adaptive increase in variability to shield important variables from effects of fatigue. We offer an interpretation of these results based on a recent development of the equilibrium-point hypothesis known as the referent configuration hypothesis. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Variance components and selection response for feather-pecking behavior in laying hens.

Science.gov (United States)

Su, G; Kjaer, J B; Sørensen, P

2005-01-01

Variance components and selection response for feather pecking behavior were studied by analyzing the data from a divergent selection experiment. An investigation indicated that a Box-Cox transformation with power lambda = -0.2 made the data approximately normally distributed and gave the best fit for the model. Variance components and selection response were estimated using Bayesian analysis with Gibbs sampling technique. The total variation was rather large for the investigated traits in both the low feather-pecking line (LP) and the high feather-pecking line (HP). Based on the mean of marginal posterior distribution, in the Box-Cox transformed scale, heritability for number of feather pecking bouts (FP bouts) was 0.174 in line LP and 0.139 in line HP. For number of feather-pecking pecks (FP pecks), heritability was 0.139 in line LP and 0.105 in line HP. No full-sib group effect and observation pen effect were found in the 2 traits. After 4 generations of selection, the total response for number of FP bouts in the transformed scale was 58 and 74% of the mean of the first generation in line LP and line HP, respectively. The total response for number of FP pecks was 47 and 46% of the mean of the first generation in line LP and line HP, respectively. The variance components and the realized selection response together suggest that genetic selection can be effective in minimizing FP behavior. This would be expected to reduce one of the major welfare problems in laying hens.

Natural genetic variation in transcriptome reflects network structure inferred with major effect mutations: insulin/TOR and associated phenotypes in Drosophila melanogaster

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Harshman Lawrence G

2009-03-01

Full Text Available Abstract Background A molecular process based genotype-to-phenotype map will ultimately enable us to predict how genetic variation among individuals results in phenotypic alterations. Building such a map is, however, far from straightforward. It requires understanding how molecular variation re-shapes developmental and metabolic networks, and how the functional state of these networks modifies phenotypes in genotype specific way. We focus on the latter problem by describing genetic variation in transcript levels of genes in the InR/TOR pathway among 72 Drosophila melanogaster genotypes. Results We observe tight co-variance in transcript levels of genes not known to influence each other through direct transcriptional control. We summarize transcriptome variation with factor analyses, and observe strong co-variance of gene expression within the dFOXO-branch and within the TOR-branch of the pathway. Finally, we investigate whether major axes of transcriptome variation shape phenotypes expected to be influenced through the InR/TOR pathway. We find limited evidence that transcript levels of individual upstream genes in the InR/TOR pathway predict fly phenotypes in expected ways. However, there is no evidence that these effects are mediated through the major axes of downstream transcriptome variation. Conclusion In summary, our results question the assertion of the 'sparse' nature of genetic networks, while validating and extending candidate gene approaches in the analyses of complex traits.

Least-squares variance component estimation

NARCIS (Netherlands)

Teunissen, P.J.G.; Amiri-Simkooei, A.R.

2007-01-01

Least-squares variance component estimation (LS-VCE) is a simple, flexible and attractive method for the estimation of unknown variance and covariance components. LS-VCE is simple because it is based on the well-known principle of LS; it is flexible because it works with a user-defined weight

Oxidative stress and hemoglobin-cholesterol adduct in renal patients with different LDL phenotypes.

Science.gov (United States)

Miljkovic, Milica; Kotur-Stevuljevic, Jelena; Stefanovic, Aleksandra; Zeljkovic, Aleksandra; Vekic, Jelena; Gojkovic, Tamara; Bogavac-Stanojevic, Natasa; Nikolic, Milan; Simic-Ogrizovic, Sanja; Spasojevic-Kalimanovska, Vesna; Jelic-Ivanovic, Zorana

2016-10-01

Unfavorable lipid profile is a major risk factor for cardiovascular disease in renal pathology. In this study, we compared chronic renal patients and healthy controls with different LDL phenotypes (A or B) in respect of various biochemical parameters related to cardiovascular disease. Oxidative stress and anti-oxidative defense parameters [thiobarbituric acid-reacting substances (TBARS), total oxidative status (TOS), total anti-oxidative status (TAS), total protein sulfhydryl (-SH) groups], as well as red blood cell cholesterol distribution were assessed in 40 renal patients and 40 control subjects by standardized assays. LDL particle diameters were determined by polyacrylamide gradient gel electrophoresis. LDL particles are subdivided according to their size into large LDL A phenotype (diameter >25.5 nm) and small LDL B phenotype (diameter ≤25.5 nm). Renal patients with LDL A phenotype had increased oxidative stress (TOS: p LDL phenotype. A notable decrease in hemoglobin-cholesterol adduct was detected in patients with LDL A phenotype (p LDL B phenotype (p LDL B phenotype was characterized with increased TBARS (p LDL A phenotype in control group. Increased oxidative stress, decreased anti-oxidative defense followed with unfavorable changes in hemoglobin-cholesterol binding capacity, could have important influence on cardiovascular disease risk in renal patients regardless of LDL phenotype.

Is there any relationship between haptoglobin phenotypes and ...

African Journals Online (AJOL)

This study was conducted to examine the possible association between Haptoglobin (Hp) phenotypes and diabetes retinopathy in some Ghanaians to determine whether a specific Hp phenotype predisposes diabetics to retinopathy. A total of 110 diabetics were enrolled into the study. Blood samples were taken from each ...

Ulnar variance: its relationship to ulnar foveal morphology and forearm kinematics.

Science.gov (United States)

Kataoka, Toshiyuki; Moritomo, Hisao; Omokawa, Shohei; Iida, Akio; Murase, Tsuyoshi; Sugamoto, Kazuomi

2012-04-01

It is unclear how individual differences in the anatomy of the distal ulna affect kinematics and pathology of the distal radioulnar joint. This study evaluated how ulnar variance relates to ulnar foveal morphology and the pronosupination axis of the forearm. We performed 3-dimensional computed tomography studies in vivo on 28 forearms in maximum supination and pronation to determine the anatomical center of the ulnar distal pole and the forearm pronosupination axis. We calculated the forearm pronosupination axis using a markerless bone registration technique, which determined the pronosupination center as the point where the axis emerges on the distal ulnar surface. We measured the depth of the anatomical center and classified it into 2 types: concave, with a depth of 0.8 mm or more, and flat, with a depth less than 0.8 mm. We examined whether ulnar variance correlated with foveal type and the distance between anatomical and pronosupination centers. A total of 18 cases had a concave-type fovea surrounded by the C-shaped articular facet of the distal pole, and 10 had a flat-type fovea with a flat surface without evident central depression. Ulnar variance of the flat type was 3.5 ± 1.2 mm, which was significantly greater than the 1.2 ± 1.1 mm of the concave type. Ulnar variance positively correlated with distance between the anatomical and pronosupination centers. Flat-type ulnar heads have a significantly greater ulnar variance than concave types. The pronosupination axis passes through the ulnar head more medially and farther from the anatomical center with increasing ulnar variance. This study suggests that ulnar variance is related in part to foveal morphology and pronosupination axis. This information provides a starting point for future studies investigating how foveal morphology relates to distal ulnar problems. Copyright © 2012 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

VARIABILITY IN PHENOTYPIC EXPRESSION OF SEED QUALITY TRAITS IN SOYBEAN GERMPLASM

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Aleksandra Sudarić

2017-01-01

Full Text Available The aim of this research was to determine the genetic variability of chosen soybean lines in seed quality by determining diversity in phenotypic expression of 1000 seed weight, as well as protein and oil concentrations in the seed. Field trials were set up in a randomized, complete block design with two replications, at the Agricultural Institute Osijek during three growing seasons (2010-2012. Each year, after harvest, 1000 seed weight, and protein and oil concentrations in the seed were determined. Statistical analyses of the results included: calculating basic measures of variation and analysis of variance. The analyzed data showed the existence of plant material's diversity in phenotypic expression of investigated seed quality traits, as well as the existence of statistically significant genotype and year effects.

Speed Variance and Its Influence on Accidents.

Science.gov (United States)

Garber, Nicholas J.; Gadirau, Ravi

A study was conducted to investigate the traffic engineering factors that influence speed variance and to determine to what extent speed variance affects accident rates. Detailed analyses were carried out to relate speed variance with posted speed limit, design speeds, and other traffic variables. The major factor identified was the difference…

Metformin treatment in different phenotypes of polycystic ovary syndrome.

Science.gov (United States)

Hosseini, Marzieh Agha; Alleyassin, Ashraf; Sarvi, Fatemeh; Safdarian, Leila; Kokab, Abas; Fanisalek, Mehran

2013-11-01

The aim of this study was to evaluate the effectiveness of Metformin on ovulation and eventual clinical pregnancy in different phenotypes of polycystic ovary syndrome (PCOS). A total of 359 subjects who had proven PCOS according to Rotterdam criteria were prospectively selected. Patients' PCOS phenotypes were determined and recorded. All patients were younger than 35 years. Clinical and biochemical assays in all patients were initially obtained. Then patients were divided into two separate groups. One group received both 1,500 mg of Metformin and 1 mg of folic acid per day and the other group received only 1 mg of folic acid for a total of 2 months. Subsequently, all patients underwent ovulation stimulation with 5 mg of Letrozole per day for 5 days followed by an intra-uterine insemination. Finally, ovulation and pregnancy rates were evaluated for all four PCOS phenotypes. Effect of Metformin therapy was evaluated for each group and each phenotype. The pregnancy rate in Metformin and non-Metformin groups were, respectively, as follows: in phenotype A (39.2 vs. 33.7 %, p = 0.270), phenotype B (43.8 vs. 20 %, p = 0.210), phenotype C (44 vs. 20 %, p = 0.064), and phenotype D (36.5 vs. 28.6 %, p = 0.279). Although there was a little improvement in ovulation and pregnancy rates among patients with B and C phenotypes, there was not a statistically significant difference between the two groups. Based on our study, Metformin therapy does not change the ovulation and pregnancy rate.

Longitudinal Analysis of Residual Feed Intake in Mink using Random Regression with Heterogeneous Residual Variance

DEFF Research Database (Denmark)

Shirali, Mahmoud; Nielsen, Vivi Hunnicke; Møller, Steen Henrik

Heritability of residual feed intake (RFI) increased from low to high over the growing period in male and female mink. The lowest heritability for RFI (male: 0.04 ± 0.01 standard deviation (SD); female: 0.05 ± 0.01 SD) was in early and the highest heritability (male: 0.33 ± 0.02; female: 0.34 ± 0.......02 SD) was achieved at the late growth stages. The genetic correlation between different growth stages for RFI showed a high association (0.91 to 0.98) between early and late growing periods. However, phenotypic correlations were lower from 0.29 to 0.50. The residual variances were substantially higher...

Variance estimation for complex indicators of poverty and inequality using linearization techniques

Directory of Open Access Journals (Sweden)

Guillaume Osier

2009-12-01

Full Text Available The paper presents the Eurostat experience in calculating measures of precision, including standard errors, confidence intervals and design effect coefficients - the ratio of the variance of a statistic with the actual sample design to the variance of that statistic with a simple random sample of same size - for the "Laeken" indicators, that is, a set of complex indicators of poverty and inequality which had been set out in the framework of the EU-SILC project (European Statistics on Income and Living Conditions. The Taylor linearization method (Tepping, 1968; Woodruff, 1971; Wolter, 1985; Tille, 2000 is actually a well-established method to obtain variance estimators for nonlinear statistics such as ratios, correlation or regression coefficients. It consists of approximating a nonlinear statistic with a linear function of the observations by using first-order Taylor Series expansions. Then, an easily found variance estimator of the linear approximation is used as an estimator of the variance of the nonlinear statistic. Although the Taylor linearization method handles all the nonlinear statistics which can be expressed as a smooth function of estimated totals, the approach fails to encompass the "Laeken" indicators since the latter are having more complex mathematical expressions. Consequently, a generalized linearization method (Deville, 1999, which relies on the concept of influence function (Hampel, Ronchetti, Rousseeuw and Stahel, 1986, has been implemented. After presenting the EU-SILC instrument and the main target indicators for which variance estimates are needed, the paper elaborates on the main features of the linearization approach based on influence functions. Ultimately, estimated standard errors, confidence intervals and design effect coefficients obtained from this approach are presented and discussed.

Variability of indoor and outdoor VOC measurements: An analysis using variance components

International Nuclear Information System (INIS)

Jia, Chunrong; Batterman, Stuart A.; Relyea, George E.

2012-01-01

This study examines concentrations of volatile organic compounds (VOCs) measured inside and outside of 162 residences in southeast Michigan, U.S.A. Nested analyses apportioned four sources of variation: city, residence, season, and measurement uncertainty. Indoor measurements were dominated by seasonal and residence effects, accounting for 50 and 31%, respectively, of the total variance. Contributions from measurement uncertainty (<20%) and city effects (<10%) were small. For outdoor measurements, season, city and measurement variation accounted for 43, 29 and 27% of variance, respectively, while residence location had negligible impact (<2%). These results show that, to obtain representative estimates of indoor concentrations, measurements in multiple seasons are required. In contrast, outdoor VOC concentrations can use multi-seasonal measurements at centralized locations. Error models showed that uncertainties at low concentrations might obscure effects of other factors. Variance component analyses can be used to interpret existing measurements, design effective exposure studies, and determine whether the instrumentation and protocols are satisfactory. - Highlights: ► The variability of VOC measurements was partitioned using nested analysis. ► Indoor VOCs were primarily controlled by seasonal and residence effects. ► Outdoor VOC levels were homogeneous within neighborhoods. ► Measurement uncertainty was high for many outdoor VOCs. ► Variance component analysis is useful for designing effective sampling programs. - Indoor VOC concentrations were primarily controlled by seasonal and residence effects; and outdoor concentrations were homogeneous within neighborhoods. Variance component analysis is a useful tool for designing effective sampling programs.

Volatility and variance swaps : A comparison of quantitative models to calculate the fair volatility and variance strike

OpenAIRE

Röring, Johan

2017-01-01

Volatility is a common risk measure in the field of finance that describes the magnitude of an asset’s up and down movement. From only being a risk measure, volatility has become an asset class of its own and volatility derivatives enable traders to get an isolated exposure to an asset’s volatility. Two kinds of volatility derivatives are volatility swaps and variance swaps. The problem with volatility swaps and variance swaps is that they require estimations of the future variance and volati...

Dynamic Mean-Variance Asset Allocation

OpenAIRE

Basak, Suleyman; Chabakauri, Georgy

2009-01-01

Mean-variance criteria remain prevalent in multi-period problems, and yet not much is known about their dynamically optimal policies. We provide a fully analytical characterization of the optimal dynamic mean-variance portfolios within a general incomplete-market economy, and recover a simple structure that also inherits several conventional properties of static models. We also identify a probability measure that incorporates intertemporal hedging demands and facilitates much tractability in ...

Independent genetic control of maize (Zea mays L.) kernel weight determination and its phenotypic plasticity.

Science.gov (United States)

Alvarez Prado, Santiago; Sadras, Víctor O; Borrás, Lucas

2014-08-01

Maize kernel weight (KW) is associated with the duration of the grain-filling period (GFD) and the rate of kernel biomass accumulation (KGR). It is also related to the dynamics of water and hence is physiologically linked to the maximum kernel water content (MWC), kernel desiccation rate (KDR), and moisture concentration at physiological maturity (MCPM). This work proposed that principles of phenotypic plasticity can help to consolidated the understanding of the environmental modulation and genetic control of these traits. For that purpose, a maize population of 245 recombinant inbred lines (RILs) was grown under different environmental conditions. Trait plasticity was calculated as the ratio of the variance of each RIL to the overall phenotypic variance of the population of RILs. This work found a hierarchy of plasticities: KDR ≈ GFD > MCPM > KGR > KW > MWC. There was no phenotypic and genetic correlation between traits per se and trait plasticities. MWC, the trait with the lowest plasticity, was the exception because common quantitative trait loci were found for the trait and its plasticity. Independent genetic control of a trait per se and genetic control of its plasticity is a condition for the independent evolution of traits and their plasticities. This allows breeders potentially to select for high or low plasticity in combination with high or low values of economically relevant traits. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Revealing plant cryptotypes: defining meaningful phenotypes among infinite traits.

Science.gov (United States)

Chitwood, Daniel H; Topp, Christopher N

2015-04-01

The plant phenotype is infinite. Plants vary morphologically and molecularly over developmental time, in response to the environment, and genetically. Exhaustive phenotyping remains not only out of reach, but is also the limiting factor to interpreting the wealth of genetic information currently available. Although phenotyping methods are always improving, an impasse remains: even if we could measure the entirety of phenotype, how would we interpret it? We propose the concept of cryptotype to describe latent, multivariate phenotypes that maximize the separation of a priori classes. Whether the infinite points comprising a leaf outline or shape descriptors defining root architecture, statistical methods to discern the quantitative essence of an organism will be required as we approach measuring the totality of phenotype. Copyright © 2015 Elsevier Ltd. All rights reserved.

Estimating the encounter rate variance in distance sampling

Science.gov (United States)

Fewster, R.M.; Buckland, S.T.; Burnham, K.P.; Borchers, D.L.; Jupp, P.E.; Laake, J.L.; Thomas, L.

2009-01-01

The dominant source of variance in line transect sampling is usually the encounter rate variance. Systematic survey designs are often used to reduce the true variability among different realizations of the design, but estimating the variance is difficult and estimators typically approximate the variance by treating the design as a simple random sample of lines. We explore the properties of different encounter rate variance estimators under random and systematic designs. We show that a design-based variance estimator improves upon the model-based estimator of Buckland et al. (2001, Introduction to Distance Sampling. Oxford: Oxford University Press, p. 79) when transects are positioned at random. However, if populations exhibit strong spatial trends, both estimators can have substantial positive bias under systematic designs. We show that poststratification is effective in reducing this bias. ?? 2008, The International Biometric Society.

How Reliable Are Students' Evaluations of Teaching Quality? A Variance Components Approach

Science.gov (United States)

Feistauer, Daniela; Richter, Tobias

2017-01-01

The inter-rater reliability of university students' evaluations of teaching quality was examined with cross-classified multilevel models. Students (N = 480) evaluated lectures and seminars over three years with a standardised evaluation questionnaire, yielding 4224 data points. The total variance of these student evaluations was separated into the…

Towards the ultimate variance-conserving convection scheme

International Nuclear Information System (INIS)

Os, J.J.A.M. van; Uittenbogaard, R.E.

2004-01-01

In the past various arguments have been used for applying kinetic energy-conserving advection schemes in numerical simulations of incompressible fluid flows. One argument is obeying the programmed dissipation by viscous stresses or by sub-grid stresses in Direct Numerical Simulation and Large Eddy Simulation, see e.g. [Phys. Fluids A 3 (7) (1991) 1766]. Another argument is that, according to e.g. [J. Comput. Phys. 6 (1970) 392; 1 (1966) 119], energy-conserving convection schemes are more stable i.e. by prohibiting a spurious blow-up of volume-integrated energy in a closed volume without external energy sources. In the above-mentioned references it is stated that nonlinear instability is due to spatial truncation rather than to time truncation and therefore these papers are mainly concerned with the spatial integration. In this paper we demonstrate that discretized temporal integration of a spatially variance-conserving convection scheme can induce non-energy conserving solutions. In this paper the conservation of the variance of a scalar property is taken as a simple model for the conservation of kinetic energy. In addition, the derivation and testing of a variance-conserving scheme allows for a clear definition of kinetic energy-conserving advection schemes for solving the Navier-Stokes equations. Consequently, we first derive and test a strictly variance-conserving space-time discretization for the convection term in the convection-diffusion equation. Our starting point is the variance-conserving spatial discretization of the convection operator presented by Piacsek and Williams [J. Comput. Phys. 6 (1970) 392]. In terms of its conservation properties, our variance-conserving scheme is compared to other spatially variance-conserving schemes as well as with the non-variance-conserving schemes applied in our shallow-water solver, see e.g. [Direct and Large-eddy Simulation Workshop IV, ERCOFTAC Series, Kluwer Academic Publishers, 2001, pp. 409-287

Effect of phenotype on health care costs in Crohn's disease: A European study using the Montreal classification.

Science.gov (United States)

Odes, Selwyn; Vardi, Hillel; Friger, Michael; Wolters, Frank; Hoie, Ole; Moum, Bjørn; Bernklev, Tomm; Yona, Hagit; Russel, Maurice; Munkholm, Pia; Langholz, Ebbe; Riis, Lene; Politi, Patrizia; Bondini, Paolo; Tsianos, Epameinondas; Katsanos, Kostas; Clofent, Juan; Vermeire, Severine; Freitas, João; Mouzas, Iannis; Limonard, Charles; O'Morain, Colm; Monteiro, Estela; Fornaciari, Giovanni; Vatn, Morten; Stockbrugger, Reinhold

2007-12-01

Crohn's disease (CD) is a chronic inflammation of the gastrointestinal tract associated with life-long high health care costs. We aimed to determine the effect of disease phenotype on cost. Clinical and economic data of a community-based CD cohort with 10-year follow-up were analyzed retrospectively in relation to Montreal classification phenotypes. In 418 patients, mean total costs of health care for the behavior phenotypes were: nonstricturing-nonpenetrating 1690, stricturing 2081, penetrating 3133 and penetrating-with-perianal-fistula 3356 €/patient-phenotype-year (P<0.001), and mean costs of surgical hospitalization 215, 751, 1293 and 1275 €/patient-phenotype-year respectively (P<0.001). Penetrating-with-perianal-fistula patients incurred significantly greater expenses than penetrating patients for total care, diagnosis and drugs, but not surgical hospitalization. Total costs were similar in the location phenotypes: ileum 1893, colon 1748, ileo-colonic 2010 and upper gastrointestinal tract 1758 €/patient-phenotype-year, but surgical hospitalization costs differed significantly, 558, 209, 492 and 542 €/patient-phenotype-year respectively (P<0.001). By multivariate analysis, the behavior phenotype significantly impacted total, medical and surgical hospitalization costs, whereas the location phenotype affected only surgical costs. Younger age at diagnosis predicted greater surgical expenses. Behavior is the dominant phenotype driving health care cost. Use of the Montreal classification permits detection of cost differences caused by perianal fistula.

On the noise variance of a digital mammography system

International Nuclear Information System (INIS)

Burgess, Arthur

2004-01-01

A recent paper by Cooper et al. [Med. Phys. 30, 2614-2621 (2003)] contains some apparently anomalous results concerning the relationship between pixel variance and x-ray exposure for a digital mammography system. They found an unexpected peak in a display domain pixel variance plot as a function of 1/mAs (their Fig. 5) with a decrease in the range corresponding to high display data values, corresponding to low x-ray exposures. As they pointed out, if the detector response is linear in exposure and the transformation from raw to display data scales is logarithmic, then pixel variance should be a monotonically increasing function in the figure. They concluded that the total system transfer curve, between input exposure and display image data values, is not logarithmic over the full exposure range. They separated data analysis into two regions and plotted the logarithm of display image pixel variance as a function of the logarithm of the mAs used to produce the phantom images. They found a slope of minus one for high mAs values and concluded that the transfer function is logarithmic in this region. They found a slope of 0.6 for the low mAs region and concluded that the transfer curve was neither linear nor logarithmic for low exposure values. It is known that the digital mammography system investigated by Cooper et al. has a linear relationship between exposure and raw data values [Vedantham et al., Med. Phys. 27, 558-567 (2000)]. The purpose of this paper is to show that the variance effect found by Cooper et al. (their Fig. 5) arises because the transformation from the raw data scale (14 bits) to the display scale (12 bits), for the digital mammography system they investigated, is not logarithmic for raw data values less than about 300 (display data values greater than about 3300). At low raw data values the transformation is linear and prevents over-ranging of the display data scale. Parametric models for the two transformations will be presented. Results of pixel

The Distribution of the Sample Minimum-Variance Frontier

OpenAIRE

Raymond Kan; Daniel R. Smith

2008-01-01

In this paper, we present a finite sample analysis of the sample minimum-variance frontier under the assumption that the returns are independent and multivariate normally distributed. We show that the sample minimum-variance frontier is a highly biased estimator of the population frontier, and we propose an improved estimator of the population frontier. In addition, we provide the exact distribution of the out-of-sample mean and variance of sample minimum-variance portfolios. This allows us t...

Variance decomposition of protein profiles from antibody arrays using a longitudinal twin model

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Kato Bernet S

2011-11-01

Full Text Available Abstract Background The advent of affinity-based proteomics technologies for global protein profiling provides the prospect of finding new molecular biomarkers for common, multifactorial disorders. The molecular phenotypes obtained from studies on such platforms are driven by multiple sources, including genetic, environmental, and experimental components. In characterizing the contribution of different sources of variation to the measured phenotypes, the aim is to facilitate the design and interpretation of future biomedical studies employing exploratory and multiplexed technologies. Thus, biometrical genetic modelling of twin or other family data can be used to decompose the variation underlying a phenotype into biological and experimental components. Results Using antibody suspension bead arrays and antibodies from the Human Protein Atlas, we study unfractionated serum from a longitudinal study on 154 twins. In this study, we provide a detailed description of how the variation in a molecular phenotype in terms of protein profile can be decomposed into familial i.e. genetic and common environmental; individual environmental, short-term biological and experimental components. The results show that across 69 antibodies analyzed in the study, the median proportion of the total variation explained by familial sources is 12% (IQR 1-22%, and the median proportion of the total variation attributable to experimental sources is 63% (IQR 53-72%. Conclusion The variability analysis of antibody arrays highlights the importance to consider variability components and their relative contributions when designing and evaluating studies for biomarker discoveries with exploratory, high-throughput and multiplexed methods.

Discrete and continuous time dynamic mean-variance analysis

OpenAIRE

Reiss, Ariane

1999-01-01

Contrary to static mean-variance analysis, very few papers have dealt with dynamic mean-variance analysis. Here, the mean-variance efficient self-financing portfolio strategy is derived for n risky assets in discrete and continuous time. In the discrete setting, the resulting portfolio is mean-variance efficient in a dynamic sense. It is shown that the optimal strategy for n risky assets may be dominated if the expected terminal wealth is constrained to exactly attain a certain goal instead o...

Swarm based mean-variance mapping optimization (MVMOS) for solving economic dispatch

Science.gov (United States)

Khoa, T. H.; Vasant, P. M.; Singh, M. S. Balbir; Dieu, V. N.

2014-10-01

The economic dispatch (ED) is an essential optimization task in the power generation system. It is defined as the process of allocating the real power output of generation units to meet required load demand so as their total operating cost is minimized while satisfying all physical and operational constraints. This paper introduces a novel optimization which named as Swarm based Mean-variance mapping optimization (MVMOS). The technique is the extension of the original single particle mean-variance mapping optimization (MVMO). Its features make it potentially attractive algorithm for solving optimization problems. The proposed method is implemented for three test power systems, including 3, 13 and 20 thermal generation units with quadratic cost function and the obtained results are compared with many other methods available in the literature. Test results have indicated that the proposed method can efficiently implement for solving economic dispatch.

Revision: Variance Inflation in Regression

Directory of Open Access Journals (Sweden)

D. R. Jensen

2013-01-01

the intercept; and (iv variance deflation may occur, where ill-conditioned data yield smaller variances than their orthogonal surrogates. Conventional VIFs have all regressors linked, or none, often untenable in practice. Beyond these, our models enable the unlinking of regressors that can be unlinked, while preserving dependence among those intrinsically linked. Moreover, known collinearity indices are extended to encompass angles between subspaces of regressors. To reaccess ill-conditioned data, we consider case studies ranging from elementary examples to data from the literature.

A comparison of phenotypic variation and covariation patterns and the role of phylogeny, ecology, and ontogeny during cranial evolution of new world monkeys.

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Marroig, G; Cheverud, J M

2001-12-01

Similarity of genetic and phenotypic variation patterns among populations is important for making quantitative inferences about past evolutionary forces acting to differentiate populations and for evaluating the evolution of relationships among traits in response to new functional and developmental relationships. Here, phenotypic co variance and correlation structure is compared among Platyrrhine Neotropical primates. Comparisons range from among species within a genus to the superfamily level. Matrix correlation followed by Mantel's test and vector correlation among responses to random natural selection vectors (random skewers) were used to compare correlation and variance/covariance matrices of 39 skull traits. Sampling errors involved in matrix estimates were taken into account in comparisons using matrix repeatability to set upper limits for each pairwise comparison. Results indicate that covariance structure is not strictly constant but that the amount of variance pattern divergence observed among taxa is generally low and not associated with taxonomic distance. Specific instances of divergence are identified. There is no correlation between the amount of divergence in covariance patterns among the 16 genera and their phylogenetic distance derived from a conjoint analysis of four already published nuclear gene datasets. In contrast, there is a significant correlation between phylogenetic distance and morphological distance (Mahalanobis distance among genus centroids). This result indicates that while the phenotypic means were evolving during the last 30 millions years of New World monkey evolution, phenotypic covariance structures of Neotropical primate skulls have remained relatively consistent. Neotropical primates can be divided into four major groups based on their feeding habits (fruit-leaves, seed-fruits, insect-fruits, and gum-insect-fruits). Differences in phenotypic covariance structure are correlated with differences in feeding habits, indicating

Epigenetic marks: regulators of livestock phenotypes and conceivable sources of missing variation in livestock improvement programs

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Eveline M Ibeagha-Awemu

2015-09-01

Full Text Available Improvement in animal productivity has been achieved over the years through careful breeding and selection programs. Today, variations in the genome are gaining increasing importance in livestock improvement strategies. Genomic information alone however explains only a part of the phenotypic variance in traits. It is likely that a portion of the unaccounted variance is embedded in the epigenome. The epigenome encompasses epigenetic marks such as DNA methylation, histone tail modifications, chromatin remodeling and other molecules that can transmit epigenetic information such as non-coding RNA species. Epigenetic factors respond to external or internal environmental cues such as nutrition, pathogens and climate, and have the ability to change gene expression leading to emergence of specific phenotypes. Accumulating evidence shows that epigenetic marks influence gene expression and phenotypic outcome in livestock species. This review examines available evidence of the influence of epigenetic marks on livestock (cattle, sheep, goat and pig traits and discusses the potential for consideration of epigenetic markers in livestock improvement programs. However, epigenetic research activities on farm animal species are currently limited partly due to lack of recognition, funding and a global network of researchers. Therefore, considerable less attention has been given to epigenetic research in livestock species in comparison to extensive work in humans and model organisms. Elucidating therefore the epigenetic determinants of animal diseases and complex traits may represent one of the principal challenges to use epigenetic markers for further improvement of animal productivity.

Variance estimation for generalized Cavalieri estimators

OpenAIRE

Johanna Ziegel; Eva B. Vedel Jensen; Karl-Anton Dorph-Petersen

2011-01-01

The precision of stereological estimators based on systematic sampling is of great practical importance. This paper presents methods of data-based variance estimation for generalized Cavalieri estimators where errors in sampling positions may occur. Variance estimators are derived under perturbed systematic sampling, systematic sampling with cumulative errors and systematic sampling with random dropouts. Copyright 2011, Oxford University Press.

Influence of Family Structure on Variance Decomposition

DEFF Research Database (Denmark)

Edwards, Stefan McKinnon; Sarup, Pernille Merete; Sørensen, Peter

Partitioning genetic variance by sets of randomly sampled genes for complex traits in D. melanogaster and B. taurus, has revealed that population structure can affect variance decomposition. In fruit flies, we found that a high likelihood ratio is correlated with a high proportion of explained ge...... capturing pure noise. Therefore it is necessary to use both criteria, high likelihood ratio in favor of a more complex genetic model and proportion of genetic variance explained, to identify biologically important gene groups...

Multiperiod Mean-Variance Portfolio Optimization via Market Cloning

International Nuclear Information System (INIS)

Ankirchner, Stefan; Dermoune, Azzouz

2011-01-01

The problem of finding the mean variance optimal portfolio in a multiperiod model can not be solved directly by means of dynamic programming. In order to find a solution we therefore first introduce independent market clones having the same distributional properties as the original market, and we replace the portfolio mean and variance by their empirical counterparts. We then use dynamic programming to derive portfolios maximizing a weighted sum of the empirical mean and variance. By letting the number of market clones converge to infinity we are able to solve the original mean variance problem.

Multiperiod Mean-Variance Portfolio Optimization via Market Cloning

Energy Technology Data Exchange (ETDEWEB)

Ankirchner, Stefan, E-mail: ankirchner@hcm.uni-bonn.de [Rheinische Friedrich-Wilhelms-Universitaet Bonn, Institut fuer Angewandte Mathematik, Hausdorff Center for Mathematics (Germany); Dermoune, Azzouz, E-mail: Azzouz.Dermoune@math.univ-lille1.fr [Universite des Sciences et Technologies de Lille, Laboratoire Paul Painleve UMR CNRS 8524 (France)

2011-08-15

The problem of finding the mean variance optimal portfolio in a multiperiod model can not be solved directly by means of dynamic programming. In order to find a solution we therefore first introduce independent market clones having the same distributional properties as the original market, and we replace the portfolio mean and variance by their empirical counterparts. We then use dynamic programming to derive portfolios maximizing a weighted sum of the empirical mean and variance. By letting the number of market clones converge to infinity we are able to solve the original mean variance problem.

Holistic and component plant phenotyping using temporal image sequence.

Science.gov (United States)

Das Choudhury, Sruti; Bashyam, Srinidhi; Qiu, Yumou; Samal, Ashok; Awada, Tala

2018-01-01

Image-based plant phenotyping facilitates the extraction of traits noninvasively by analyzing large number of plants in a relatively short period of time. It has the potential to compute advanced phenotypes by considering the whole plant as a single object (holistic phenotypes) or as individual components, i.e., leaves and the stem (component phenotypes), to investigate the biophysical characteristics of the plants. The emergence timing, total number of leaves present at any point of time and the growth of individual leaves during vegetative stage life cycle of the maize plants are significant phenotypic expressions that best contribute to assess the plant vigor. However, image-based automated solution to this novel problem is yet to be explored. A set of new holistic and component phenotypes are introduced in this paper. To compute the component phenotypes, it is essential to detect the individual leaves and the stem. Thus, the paper introduces a novel method to reliably detect the leaves and the stem of the maize plants by analyzing 2-dimensional visible light image sequences captured from the side using a graph based approach. The total number of leaves are counted and the length of each leaf is measured for all images in the sequence to monitor leaf growth. To evaluate the performance of the proposed algorithm, we introduce University of Nebraska-Lincoln Component Plant Phenotyping Dataset (UNL-CPPD) and provide ground truth to facilitate new algorithm development and uniform comparison. The temporal variation of the component phenotypes regulated by genotypes and environment (i.e., greenhouse) are experimentally demonstrated for the maize plants on UNL-CPPD. Statistical models are applied to analyze the greenhouse environment impact and demonstrate the genetic regulation of the temporal variation of the holistic phenotypes on the public dataset called Panicoid Phenomap-1. The central contribution of the paper is a novel computer vision based algorithm for

Models of Postural Control: Shared Variance in Joint and COM Motions.

Directory of Open Access Journals (Sweden)

Melissa C Kilby

Full Text Available This paper investigated the organization of the postural control system in human upright stance. To this aim the shared variance between joint and 3D total body center of mass (COM motions was analyzed using multivariate canonical correlation analysis (CCA. The CCA was performed as a function of established models of postural control that varied in their joint degrees of freedom (DOF, namely, an inverted pendulum ankle model (2DOF, ankle-hip model (4DOF, ankle-knee-hip model (5DOF, and ankle-knee-hip-neck model (7DOF. Healthy young adults performed various postural tasks (two-leg and one-leg quiet stances, voluntary AP and ML sway on a foam and rigid surface of support. Based on CCA model selection procedures, the amount of shared variance between joint and 3D COM motions and the cross-loading patterns we provide direct evidence of the contribution of multi-DOF postural control mechanisms to human balance. The direct model fitting of CCA showed that incrementing the DOFs in the model through to 7DOF was associated with progressively enhanced shared variance with COM motion. In the 7DOF model, the first canonical function revealed more active involvement of all joints during more challenging one leg stances and dynamic posture tasks. Furthermore, the shared variance was enhanced during the dynamic posture conditions, consistent with a reduction of dimension. This set of outcomes shows directly the degeneracy of multivariate joint regulation in postural control that is influenced by stance and surface of support conditions.

A family-based joint test for mean and variance heterogeneity for quantitative traits.

Science.gov (United States)

Cao, Ying; Maxwell, Taylor J; Wei, Peng

2015-01-01

Traditional quantitative trait locus (QTL) analysis focuses on identifying loci associated with mean heterogeneity. Recent research has discovered loci associated with phenotype variance heterogeneity (vQTL), which is important in studying genetic association with complex traits, especially for identifying gene-gene and gene-environment interactions. While several tests have been proposed to detect vQTL for unrelated individuals, there are no tests for related individuals, commonly seen in family-based genetic studies. Here we introduce a likelihood ratio test (LRT) for identifying mean and variance heterogeneity simultaneously or for either effect alone, adjusting for covariates and family relatedness using a linear mixed effect model approach. The LRT test statistic for normally distributed quantitative traits approximately follows χ(2)-distributions. To correct for inflated Type I error for non-normally distributed quantitative traits, we propose a parametric bootstrap-based LRT that removes the best linear unbiased prediction (BLUP) of family random effect. Simulation studies show that our family-based test controls Type I error and has good power, while Type I error inflation is observed when family relatedness is ignored. We demonstrate the utility and efficiency gains of the proposed method using data from the Framingham Heart Study to detect loci associated with body mass index (BMI) variability. © 2014 John Wiley & Sons Ltd/University College London.

Minimum Variance Portfolios in the Brazilian Equity Market

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Alexandre Rubesam

2013-03-01

Full Text Available We investigate minimum variance portfolios in the Brazilian equity market using different methods to estimate the covariance matrix, from the simple model of using the sample covariance to multivariate GARCH models. We compare the performance of the minimum variance portfolios to those of the following benchmarks: (i the IBOVESPA equity index, (ii an equally-weighted portfolio, (iii the maximum Sharpe ratio portfolio and (iv the maximum growth portfolio. Our results show that the minimum variance portfolio has higher returns with lower risk compared to the benchmarks. We also consider long-short 130/30 minimum variance portfolios and obtain similar results. The minimum variance portfolio invests in relatively few stocks with low βs measured with respect to the IBOVESPA index, being easily replicable by individual and institutional investors alike.

Genetic variance in micro-environmental sensitivity for milk and milk quality in Walloon Holstein cattle.

Science.gov (United States)

Vandenplas, J; Bastin, C; Gengler, N; Mulder, H A

2013-09-01

Animals that are robust to environmental changes are desirable in the current dairy industry. Genetic differences in micro-environmental sensitivity can be studied through heterogeneity of residual variance between animals. However, residual variance between animals is usually assumed to be homogeneous in traditional genetic evaluations. The aim of this study was to investigate genetic heterogeneity of residual variance by estimating variance components in residual variance for milk yield, somatic cell score, contents in milk (g/dL) of 2 groups of milk fatty acids (i.e., saturated and unsaturated fatty acids), and the content in milk of one individual fatty acid (i.e., oleic acid, C18:1 cis-9), for first-parity Holstein cows in the Walloon Region of Belgium. A total of 146,027 test-day records from 26,887 cows in 747 herds were available. All cows had at least 3 records and a known sire. These sires had at least 10 cows with records and each herd × test-day had at least 5 cows. The 5 traits were analyzed separately based on fixed lactation curve and random regression test-day models for the mean. Estimation of variance components was performed by running iteratively expectation maximization-REML algorithm by the implementation of double hierarchical generalized linear models. Based on fixed lactation curve test-day mean models, heritability for residual variances ranged between 1.01×10(-3) and 4.17×10(-3) for all traits. The genetic standard deviation in residual variance (i.e., approximately the genetic coefficient of variation of residual variance) ranged between 0.12 and 0.17. Therefore, some genetic variance in micro-environmental sensitivity existed in the Walloon Holstein dairy cattle for the 5 studied traits. The standard deviations due to herd × test-day and permanent environment in residual variance ranged between 0.36 and 0.45 for herd × test-day effect and between 0.55 and 0.97 for permanent environmental effect. Therefore, nongenetic effects also

Variance of a potential of mean force obtained using the weighted histogram analysis method.

Science.gov (United States)

Cukier, Robert I

2013-11-27

A potential of mean force (PMF) that provides the free energy of a thermally driven system along some chosen reaction coordinate (RC) is a useful descriptor of systems characterized by complex, high dimensional potential energy surfaces. Umbrella sampling window simulations use potential energy restraints to provide more uniform sampling along a RC so that potential energy barriers that would otherwise make equilibrium sampling computationally difficult can be overcome. Combining the results from the different biased window trajectories can be accomplished using the Weighted Histogram Analysis Method (WHAM). Here, we provide an analysis of the variance of a PMF along the reaction coordinate. We assume that the potential restraints used for each window lead to Gaussian distributions for the window reaction coordinate densities and that the data sampling in each window is from an equilibrium ensemble sampled so that successive points are statistically independent. Also, we assume that neighbor window densities overlap, as required in WHAM, and that further-than-neighbor window density overlap is negligible. Then, an analytic expression for the variance of the PMF along the reaction coordinate at a desired level of spatial resolution can be generated. The variance separates into a sum over all windows with two kinds of contributions: One from the variance of the biased window density normalized by the total biased window density and the other from the variance of the local (for each window's coordinate range) PMF. Based on the desired spatial resolution of the PMF, the former variance can be minimized relative to that from the latter. The method is applied to a model system that has features of a complex energy landscape evocative of a protein with two conformational states separated by a free energy barrier along a collective reaction coordinate. The variance can be constructed from data that is already available from the WHAM PMF construction.

Why risk is not variance: an expository note.

Science.gov (United States)

Cox, Louis Anthony Tony

2008-08-01

Variance (or standard deviation) of return is widely used as a measure of risk in financial investment risk analysis applications, where mean-variance analysis is applied to calculate efficient frontiers and undominated portfolios. Why, then, do health, safety, and environmental (HS&E) and reliability engineering risk analysts insist on defining risk more flexibly, as being determined by probabilities and consequences, rather than simply by variances? This note suggests an answer by providing a simple proof that mean-variance decision making violates the principle that a rational decisionmaker should prefer higher to lower probabilities of receiving a fixed gain, all else being equal. Indeed, simply hypothesizing a continuous increasing indifference curve for mean-variance combinations at the origin is enough to imply that a decisionmaker must find unacceptable some prospects that offer a positive probability of gain and zero probability of loss. Unlike some previous analyses of limitations of variance as a risk metric, this expository note uses only simple mathematics and does not require the additional framework of von Neumann Morgenstern utility theory.

Variance bias analysis for the Gelbard's batch method

Energy Technology Data Exchange (ETDEWEB)

Seo, Jae Uk; Shim, Hyung Jin [Seoul National Univ., Seoul (Korea, Republic of)

2014-05-15

In this paper, variances and the bias will be derived analytically when the Gelbard's batch method is applied. And then, the real variance estimated from this bias will be compared with the real variance calculated from replicas. Variance and the bias were derived analytically when the batch method was applied. If the batch method was applied to calculate the sample variance, covariance terms between tallies which exist in the batch were eliminated from the bias. With the 2 by 2 fission matrix problem, we could calculate real variance regardless of whether or not the batch method was applied. However as batch size got larger, standard deviation of real variance was increased. When we perform a Monte Carlo estimation, we could get a sample variance as the statistical uncertainty of it. However, this value is smaller than the real variance of it because a sample variance is biased. To reduce this bias, Gelbard devised the method which is called the Gelbard's batch method. It has been certificated that a sample variance get closer to the real variance when the batch method is applied. In other words, the bias get reduced. This fact is well known to everyone in the MC field. However, so far, no one has given the analytical interpretation on it.

Effect of Box-Cox transformation on power of Haseman-Elston and maximum-likelihood variance components tests to detect quantitative trait Loci.

Science.gov (United States)

Etzel, C J; Shete, S; Beasley, T M; Fernandez, J R; Allison, D B; Amos, C I

2003-01-01

Non-normality of the phenotypic distribution can affect power to detect quantitative trait loci in sib pair studies. Previously, we observed that Winsorizing the sib pair phenotypes increased the power of quantitative trait locus (QTL) detection for both Haseman-Elston (HE) least-squares tests [Hum Hered 2002;53:59-67] and maximum likelihood-based variance components (MLVC) analysis [Behav Genet (in press)]. Winsorizing the phenotypes led to a slight increase in type 1 error in H-E tests and a slight decrease in type I error for MLVC analysis. Herein, we considered transforming the sib pair phenotypes using the Box-Cox family of transformations. Data were simulated for normal and non-normal (skewed and kurtic) distributions. Phenotypic values were replaced by Box-Cox transformed values. Twenty thousand replications were performed for three H-E tests of linkage and the likelihood ratio test (LRT), the Wald test and other robust versions based on the MLVC method. We calculated the relative nominal inflation rate as the ratio of observed empirical type 1 error divided by the set alpha level (5, 1 and 0.1% alpha levels). MLVC tests applied to non-normal data had inflated type I errors (rate ratio greater than 1.0), which were controlled best by Box-Cox transformation and to a lesser degree by Winsorizing. For example, for non-transformed, skewed phenotypes (derived from a chi2 distribution with 2 degrees of freedom), the rates of empirical type 1 error with respect to set alpha level=0.01 were 0.80, 4.35 and 7.33 for the original H-E test, LRT and Wald test, respectively. For the same alpha level=0.01, these rates were 1.12, 3.095 and 4.088 after Winsorizing and 0.723, 1.195 and 1.905 after Box-Cox transformation. Winsorizing reduced inflated error rates for the leptokurtic distribution (derived from a Laplace distribution with mean 0 and variance 8). Further, power (adjusted for empirical type 1 error) at the 0.01 alpha level ranged from 4.7 to 17.3% across all tests

Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits

DEFF Research Database (Denmark)

Gebreyesus, Grum; Lund, Mogens Sandø; Buitenhuis, Albert Johannes

2017-01-01

Accurate genomic prediction requires a large reference population, which is problematic for traits that are expensive to measure. Traits related to milk protein composition are not routinely recorded due to costly procedures and are considered to be controlled by a few quantitative trait loci...... of large effect. The amount of variation explained may vary between regions leading to heterogeneous (co)variance patterns across the genome. Genomic prediction models that can efficiently take such heterogeneity of (co)variances into account can result in improved prediction reliability. In this study, we...... developed and implemented novel univariate and bivariate Bayesian prediction models, based on estimates of heterogeneous (co)variances for genome segments (BayesAS). Available data consisted of milk protein composition traits measured on cows and de-regressed proofs of total protein yield derived for bulls...

Integrating Variances into an Analytical Database

Science.gov (United States)

Sanchez, Carlos

2010-01-01

For this project, I enrolled in numerous SATERN courses that taught the basics of database programming. These include: Basic Access 2007 Forms, Introduction to Database Systems, Overview of Database Design, and others. My main job was to create an analytical database that can handle many stored forms and make it easy to interpret and organize. Additionally, I helped improve an existing database and populate it with information. These databases were designed to be used with data from Safety Variances and DCR forms. The research consisted of analyzing the database and comparing the data to find out which entries were repeated the most. If an entry happened to be repeated several times in the database, that would mean that the rule or requirement targeted by that variance has been bypassed many times already and so the requirement may not really be needed, but rather should be changed to allow the variance's conditions permanently. This project did not only restrict itself to the design and development of the database system, but also worked on exporting the data from the database to a different format (e.g. Excel or Word) so it could be analyzed in a simpler fashion. Thanks to the change in format, the data was organized in a spreadsheet that made it possible to sort the data by categories or types and helped speed up searches. Once my work with the database was done, the records of variances could be arranged so that they were displayed in numerical order, or one could search for a specific document targeted by the variances and restrict the search to only include variances that modified a specific requirement. A great part that contributed to my learning was SATERN, NASA's resource for education. Thanks to the SATERN online courses I took over the summer, I was able to learn many new things about computers and databases and also go more in depth into topics I already knew about.

Regional sensitivity analysis using revised mean and variance ratio functions

International Nuclear Information System (INIS)

Wei, Pengfei; Lu, Zhenzhou; Ruan, Wenbin; Song, Jingwen

2014-01-01

The variance ratio function, derived from the contribution to sample variance (CSV) plot, is a regional sensitivity index for studying how much the output deviates from the original mean of model output when the distribution range of one input is reduced and to measure the contribution of different distribution ranges of each input to the variance of model output. In this paper, the revised mean and variance ratio functions are developed for quantifying the actual change of the model output mean and variance, respectively, when one reduces the range of one input. The connection between the revised variance ratio function and the original one is derived and discussed. It is shown that compared with the classical variance ratio function, the revised one is more suitable to the evaluation of model output variance due to reduced ranges of model inputs. A Monte Carlo procedure, which needs only a set of samples for implementing it, is developed for efficiently computing the revised mean and variance ratio functions. The revised mean and variance ratio functions are compared with the classical ones by using the Ishigami function. At last, they are applied to a planar 10-bar structure

Detecting parent of origin and dominant QTL in a two-generation commercial poultry pedigree using variance component methodology

Directory of Open Access Journals (Sweden)

Haley Christopher S

2009-01-01

Full Text Available Abstract Introduction Variance component QTL methodology was used to analyse three candidate regions on chicken chromosomes 1, 4 and 5 for dominant and parent-of-origin QTL effects. Data were available for bodyweight and conformation score measured at 40 days from a two-generation commercial broiler dam line. One hundred dams were nested in 46 sires with phenotypes and genotypes on 2708 offspring. Linear models were constructed to simultaneously estimate fixed, polygenic and QTL effects. Different genetic models were compared using likelihood ratio test statistics derived from the comparison of full with reduced or null models. Empirical thresholds were derived by permutation analysis. Results Dominant QTL were found for bodyweight on chicken chromosome 4 and for bodyweight and conformation score on chicken chromosome 5. Suggestive evidence for a maternally expressed QTL for bodyweight and conformation score was found on chromosome 1 in a region corresponding to orthologous imprinted regions in the human and mouse. Conclusion Initial results suggest that variance component analysis can be applied within commercial populations for the direct detection of segregating dominant and parent of origin effects.

Phenotypic variability in unicellular organisms: from calcium signalling to social behaviour.

Science.gov (United States)

Vogel, David; Nicolis, Stamatios C; Perez-Escudero, Alfonso; Nanjundiah, Vidyanand; Sumpter, David J T; Dussutour, Audrey

2015-11-22

Historically, research has focused on the mean and often neglected the variance. However, variability in nature is observable at all scales: among cells within an individual, among individuals within a population and among populations within a species. A fundamental quest in biology now is to find the mechanisms that underlie variability. Here, we investigated behavioural variability in a unique unicellular organism, Physarum polycephalum. We combined experiments and models to show that variability in cell signalling contributes to major differences in behaviour underpinning some aspects of social interactions. First, following thousands of cells under various contexts, we identified distinct behavioural phenotypes: 'slow-regular-social', 'fast-regular-social' and 'fast-irregular-asocial'. Second, coupling chemical analysis and behavioural assays we found that calcium signalling is responsible for these behavioural phenotypes. Finally, we show that differences in signalling and behaviour led to alternative social strategies. Our results have considerable implications for our understanding of the emergence of variability in living organisms. © 2015 The Author(s).

Estimation of measurement variances

International Nuclear Information System (INIS)

Jaech, J.L.

1984-01-01

The estimation of measurement error parameters in safeguards systems is discussed. Both systematic and random errors are considered. A simple analysis of variances to characterize the measurement error structure with biases varying over time is presented

29 CFR 1905.5 - Effect of variances.

Science.gov (United States)

2010-07-01

...-STEIGER OCCUPATIONAL SAFETY AND HEALTH ACT OF 1970 General § 1905.5 Effect of variances. All variances... Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR... concerning a proposed penalty or period of abatement is pending before the Occupational Safety and Health...

Realized range-based estimation of integrated variance

DEFF Research Database (Denmark)

Christensen, Kim; Podolskij, Mark

2007-01-01

We provide a set of probabilistic laws for estimating the quadratic variation of continuous semimartingales with the realized range-based variance-a statistic that replaces every squared return of the realized variance with a normalized squared range. If the entire sample path of the process is a...

Evolution of phenotypic plasticity and environmental tolerance of a labile quantitative character in a fluctuating environment.

Science.gov (United States)

Lande, R

2014-05-01

Quantitative genetic models of evolution of phenotypic plasticity are used to derive environmental tolerance curves for a population in a changing environment, providing a theoretical foundation for integrating physiological and community ecology with evolutionary genetics of plasticity and norms of reaction. Plasticity is modelled for a labile quantitative character undergoing continuous reversible development and selection in a fluctuating environment. If there is no cost of plasticity, a labile character evolves expected plasticity equalling the slope of the optimal phenotype as a function of the environment. This contrasts with previous theory for plasticity influenced by the environment at a critical stage of early development determining a constant adult phenotype on which selection acts, for which the expected plasticity is reduced by the environmental predictability over the discrete time lag between development and selection. With a cost of plasticity in a labile character, the expected plasticity depends on the cost and on the environmental variance and predictability averaged over the continuous developmental time lag. Environmental tolerance curves derived from this model confirm traditional assumptions in physiological ecology and provide new insights. Tolerance curve width increases with larger environmental variance, but can only evolve within a limited range. The strength of the trade-off between tolerance curve height and width depends on the cost of plasticity. Asymmetric tolerance curves caused by male sterility at high temperature are illustrated. A simple condition is given for a large transient increase in plasticity and tolerance curve width following a sudden change in average environment. © 2014 The Author. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Variance Function Partially Linear Single-Index Models1.

Science.gov (United States)

Lian, Heng; Liang, Hua; Carroll, Raymond J

2015-01-01

We consider heteroscedastic regression models where the mean function is a partially linear single index model and the variance function depends upon a generalized partially linear single index model. We do not insist that the variance function depend only upon the mean function, as happens in the classical generalized partially linear single index model. We develop efficient and practical estimation methods for the variance function and for the mean function. Asymptotic theory for the parametric and nonparametric parts of the model is developed. Simulations illustrate the results. An empirical example involving ozone levels is used to further illustrate the results, and is shown to be a case where the variance function does not depend upon the mean function.

The genotype-phenotype map of an evolving digital organism.

Directory of Open Access Journals (Sweden)

Miguel A Fortuna

2017-02-01

Full Text Available To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences, which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.

The genotype-phenotype map of an evolving digital organism.

Science.gov (United States)

Fortuna, Miguel A; Zaman, Luis; Ofria, Charles; Wagner, Andreas

2017-02-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.

Discrete time and continuous time dynamic mean-variance analysis

OpenAIRE

Reiss, Ariane

1999-01-01

Contrary to static mean-variance analysis, very few papers have dealt with dynamic mean-variance analysis. Here, the mean-variance efficient self-financing portfolio strategy is derived for n risky assets in discrete and continuous time. In the discrete setting, the resulting portfolio is mean-variance efficient in a dynamic sense. It is shown that the optimal strategy for n risky assets may be dominated if the expected terminal wealth is constrained to exactly attain a certain goal instead o...

CMB-S4 and the hemispherical variance anomaly

Science.gov (United States)

O'Dwyer, Márcio; Copi, Craig J.; Knox, Lloyd; Starkman, Glenn D.

2017-09-01

Cosmic microwave background (CMB) full-sky temperature data show a hemispherical asymmetry in power nearly aligned with the Ecliptic. In real space, this anomaly can be quantified by the temperature variance in the Northern and Southern Ecliptic hemispheres, with the Northern hemisphere displaying an anomalously low variance while the Southern hemisphere appears unremarkable [consistent with expectations from the best-fitting theory, Lambda Cold Dark Matter (ΛCDM)]. While this is a well-established result in temperature, the low signal-to-noise ratio in current polarization data prevents a similar comparison. This will change with a proposed ground-based CMB experiment, CMB-S4. With that in mind, we generate realizations of polarization maps constrained by the temperature data and predict the distribution of the hemispherical variance in polarization considering two different sky coverage scenarios possible in CMB-S4: full Ecliptic north coverage and just the portion of the North that can be observed from a ground-based telescope at the high Chilean Atacama plateau. We find that even in the set of realizations constrained by the temperature data, the low Northern hemisphere variance observed in temperature is not expected in polarization. Therefore, observing an anomalously low variance in polarization would make the hypothesis that the temperature anomaly is simply a statistical fluke more unlikely and thus increase the motivation for physical explanations. We show, within ΛCDM, how variance measurements in both sky coverage scenarios are related. We find that the variance makes for a good statistic in cases where the sky coverage is limited, however, full northern coverage is still preferable.

Phenotypic and genetic diversity in Sinorhizobium meliloti and S. medicae from drought and salt affected regions of Morocco

Directory of Open Access Journals (Sweden)

Udupa Sripada M

2010-01-01

Full Text Available Abstract Background Sinorhizobium meliloti and S. medicae are symbiotic nitrogen fixing bacteria in root nodules of forage legume alfalfa (Medicago sativa L.. In Morocco, alfalfa is usually grown in marginal soils of arid and semi-arid regions frequently affected by drought, extremes of temperature and soil pH, soil salinity and heavy metals, which affect biological nitrogen fixing ability of rhizobia and productivity of the host. This study examines phenotypic diversity for tolerance to the above stresses and genotypic diversity at Repetitive Extragenic Pallindromic DNA regions of Sinorhizobium nodulating alfalfa, sampled from marginal soils of arid and semi-arid regions of Morocco. Results RsaI digestion of PCR amplified 16S rDNA of the 157 sampled isolates, assigned 136 isolates as S. meliloti and the rest as S. medicae. Further phenotyping of these alfalfa rhizobia for tolerance to the environmental stresses revealed a large degree of variation: 55.41%, 82.16%, 57.96% and 3.18% of the total isolates were tolerant to NaCl (>513 mM, water stress (-1.5 MPa, high temperature (40°C and low pH (3.5, respectively. Sixty-seven isolates of S. meliloti and thirteen isolates of S. medicae that were tolerant to salinity were also tolerant to water stress. Most of the isolates of the two species showed tolerance to heavy metals (Cd, Mn and Zn and antibiotics (chloramphenicol, spectinomycin, streptomycin and tetracycline. The phenotypic clusters observed by the cluster analysis clearly showed adaptations of the S. meliloti and S. medicae strains to the multiple stresses. Genotyping with rep-PCR revealed higher genetic diversity within these phenotypic clusters and classified all the 157 isolates into 148 genotypes. No relationship between genotypic profiles and the phenotypes was observed. The Analysis of Molecular Variance revealed that largest proportion of significant (P Conclusion High degree of phenotypic and genotypic diversity is present in S

Expected Stock Returns and Variance Risk Premia

DEFF Research Database (Denmark)

Bollerslev, Tim; Zhou, Hao

risk premium with the P/E ratio results in an R2 for the quarterly returns of more than twenty-five percent. The results depend crucially on the use of "model-free", as opposed to standard Black-Scholes, implied variances, and realized variances constructed from high-frequency intraday, as opposed...

Allowable variance set on left ventricular function parameter

International Nuclear Information System (INIS)

Zhou Li'na; Qi Zhongzhi; Zeng Yu; Ou Xiaohong; Li Lin

2010-01-01

Purpose: To evaluate the influence of allowable Variance settings on left ventricular function parameter of the arrhythmia patients during gated myocardial perfusion imaging. Method: 42 patients with evident arrhythmia underwent myocardial perfusion SPECT, 3 different allowable variance with 20%, 60%, 100% would be set before acquisition for every patients,and they will be acquired simultaneously. After reconstruction by Astonish, end-diastole volume(EDV) and end-systolic volume (ESV) and left ventricular ejection fraction (LVEF) would be computed with Quantitative Gated SPECT(QGS). Using SPSS software EDV, ESV, EF values of analysis of variance. Result: there is no statistical difference between three groups. Conclusion: arrhythmia patients undergo Gated myocardial perfusion imaging, Allowable Variance settings on EDV, ESV, EF value does not have a statistical meaning. (authors)

Deviation of the Variances of Classical Estimators and Negative Integer Moment Estimator from Minimum Variance Bound with Reference to Maxwell Distribution

Directory of Open Access Journals (Sweden)

G. R. Pasha

2006-07-01

Full Text Available In this paper, we present that how much the variances of the classical estimators, namely, maximum likelihood estimator and moment estimator deviate from the minimum variance bound while estimating for the Maxwell distribution. We also sketch this difference for the negative integer moment estimator. We note the poor performance of the negative integer moment estimator in the said consideration while maximum likelihood estimator attains minimum variance bound and becomes an attractive choice.

Towards a mathematical foundation of minimum-variance theory

Energy Technology Data Exchange (ETDEWEB)

Feng Jianfeng [COGS, Sussex University, Brighton (United Kingdom); Zhang Kewei [SMS, Sussex University, Brighton (United Kingdom); Wei Gang [Mathematical Department, Baptist University, Hong Kong (China)

2002-08-30

The minimum-variance theory which accounts for arm and eye movements with noise signal inputs was proposed by Harris and Wolpert (1998 Nature 394 780-4). Here we present a detailed theoretical analysis of the theory and analytical solutions of the theory are obtained. Furthermore, we propose a new version of the minimum-variance theory, which is more realistic for a biological system. For the new version we show numerically that the variance is considerably reduced. (author)

Measuring kinetics of complex single ion channel data using mean-variance histograms.

Science.gov (United States)

Patlak, J B

1993-07-01

The measurement of single ion channel kinetics is difficult when those channels exhibit subconductance events. When the kinetics are fast, and when the current magnitudes are small, as is the case for Na+, Ca2+, and some K+ channels, these difficulties can lead to serious errors in the estimation of channel kinetics. I present here a method, based on the construction and analysis of mean-variance histograms, that can overcome these problems. A mean-variance histogram is constructed by calculating the mean current and the current variance within a brief "window" (a set of N consecutive data samples) superimposed on the digitized raw channel data. Systematic movement of this window over the data produces large numbers of mean-variance pairs which can be assembled into a two-dimensional histogram. Defined current levels (open, closed, or sublevel) appear in such plots as low variance regions. The total number of events in such low variance regions is estimated by curve fitting and plotted as a function of window width. This function decreases with the same time constants as the original dwell time probability distribution for each of the regions. The method can therefore be used: 1) to present a qualitative summary of the single channel data from which the signal-to-noise ratio, open channel noise, steadiness of the baseline, and number of conductance levels can be quickly determined; 2) to quantify the dwell time distribution in each of the levels exhibited. In this paper I present the analysis of a Na+ channel recording that had a number of complexities. The signal-to-noise ratio was only about 8 for the main open state, open channel noise, and fast flickers to other states were present, as were a substantial number of subconductance states. "Standard" half-amplitude threshold analysis of these data produce open and closed time histograms that were well fitted by the sum of two exponentials, but with apparently erroneous time constants, whereas the mean-variance

Direct encoding of orientation variance in the visual system.

Science.gov (United States)

Norman, Liam J; Heywood, Charles A; Kentridge, Robert W

2015-01-01

Our perception of regional irregularity, an example of which is orientation variance, seems effortless when we view two patches of texture that differ in this attribute. Little is understood, however, of how the visual system encodes a regional statistic like orientation variance, but there is some evidence to suggest that it is directly encoded by populations of neurons tuned broadly to high or low levels. The present study shows that selective adaptation to low or high levels of variance results in a perceptual aftereffect that shifts the perceived level of variance of a subsequently viewed texture in the direction away from that of the adapting stimulus (Experiments 1 and 2). Importantly, the effect is durable across changes in mean orientation, suggesting that the encoding of orientation variance is independent of global first moment orientation statistics (i.e., mean orientation). In Experiment 3 it was shown that the variance-specific aftereffect did not show signs of being encoded in a spatiotopic reference frame, similar to the equivalent aftereffect of adaptation to the first moment orientation statistic (the tilt aftereffect), which is represented in the primary visual cortex and exists only in retinotopic coordinates. Experiment 4 shows that a neuropsychological patient with damage to ventral areas of the cortex but spared intact early areas retains sensitivity to orientation variance. Together these results suggest that orientation variance is encoded directly by the visual system and possibly at an early cortical stage.

Recognition of emotional facial expressions and broad autism phenotype in parents of children diagnosed with autistic spectrum disorder.

Science.gov (United States)

Kadak, Muhammed Tayyib; Demirel, Omer Faruk; Yavuz, Mesut; Demir, Türkay

2014-07-01

Research findings debate about features of broad autism phenotype. In this study, we tested whether parents of children with autism have problems recognizing emotional facial expression and the contribution of such an impairment to the broad phenotype of autism. Seventy-two parents of children with autistic spectrum disorder and 38 parents of control group participated in the study. Broad autism features was measured with Autism Quotient (AQ). Recognition of Emotional Face Expression Test was assessed with the Emotion Recognition Test, consisting a set of photographs from Ekman & Friesen's. In a two-tailed analysis of variance of AQ, there was a significant difference for social skills (F(1, 106)=6.095; p<.05). Analyses of variance revealed significant difference in the recognition of happy, surprised and neutral expressions (F(1, 106)=4.068, p=.046; F(1, 106)=4.068, p=.046; F(1, 106)=6.064, p=.016). According to our findings, social impairment could be considered a characteristic feature of BAP. ASD parents had difficulty recognizing neutral expressions, suggesting that ASD parents may have impaired recognition of ambiguous expressions as do autistic children. Copyright © 2014 Elsevier Inc. All rights reserved.

Network Structure and Biased Variance Estimation in Respondent Driven Sampling.

Science.gov (United States)

Verdery, Ashton M; Mouw, Ted; Bauldry, Shawn; Mucha, Peter J

2015-01-01

This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network.

Comparative analysis of distinct phenotypes in gambling disorder based on gambling preferences.

Science.gov (United States)

Moragas, Laura; Granero, Roser; Stinchfield, Randy; Fernández-Aranda, Fernando; Fröberg, Frida; Aymamí, Neus; Gómez-Peña, Mónica; Fagundo, Ana B; Islam, Mohammed A; Del Pino-Gutiérrez, Amparo; Agüera, Zaida; Savvidou, Lamprini G; Arcelus, Jon; Witcomb, Gemma L; Sauchelli, Sarah; Menchón, José M; Jiménez-Murcia, Susana

2015-04-15

Studies examining gambling preferences have identified the importance of the type of gambling practiced on distinct individual profiles. The objectives were to compare clinical, psychopathological and personality variables between two different groups of individuals with a gambling disorder (strategic and non-strategic gamblers) and to evaluate the statistical prediction capacity of these preferences with respect to the severity of the disorder. A total sample of 2010 treatment-seeking patients with a gambling disorder participated in this stand-alone study. All were recruited from a single Pathological Gambling Unit in Spain (1709 strategic and 301 non-strategic gamblers). The design of the study was cross-sectional and data were collected at the start of treatment. Data was analysed using logistic regression for binary outcomes and analysis of variance (ANOVA) for quantitative responses. There were significant differences in several socio-demographic and clinical variables, as well as in personality traits (novelty seeking and cooperativeness). Multiple regression analysis showed harm avoidance and self-directedness were the main predictors of gambling severity and psychopathology, while age at assessment and age of onset of gambling behaviour were predictive of gambling severity. Strategic gambling (as opposed to non-strategic) was significantly associated with clinical outcomes, but the effect size of the relationships was small. It is possible to identify distinct phenotypes depending on the preference of gambling. While these phenotypes differ in relation to the severity of the gambling disorder, psychopathology and personality traits, they can be useful from a clinical and therapeutic perspective in enabling risk factors to be identified and prevention programs targeting specific individual profiles to be developed.

Local variances in biomonitoring

International Nuclear Information System (INIS)

Wolterbeek, H.Th; Verburg, T.G.

2001-01-01

The present study was undertaken to explore possibilities to judge survey quality on basis of a limited and restricted number of a-priori observations. Here, quality is defined as the ratio between survey and local variance (signal-to-noise ratio). The results indicate that the presented surveys do not permit such judgement; the discussion also suggests that the 5-fold local sampling strategies do not merit any sound judgement. As it stands, uncertainties in local determinations may largely obscure possibilities to judge survey quality. The results further imply that surveys will benefit from procedures, controls and approaches in sampling and sample handling, to assess both average, variance and the nature of the distribution of elemental concentrations in local sites. This reasoning is compatible with the idea of the site as a basic homogeneous survey unit, which is implicitly and conceptually underlying any survey performed. (author)

Variance components estimation for farrowing traits of three purebred pigs in Korea

Directory of Open Access Journals (Sweden)

Bryan Irvine Lopez

2017-09-01

Full Text Available Objective This study was conducted to estimate breed-specific variance components for total number born (TNB, number born alive (NBA and mortality rate from birth through weaning including stillbirths (MORT of three main swine breeds in Korea. In addition, the importance of including maternal genetic and service sire effects in estimation models was evaluated. Methods Records of farrowing traits from 6,412 Duroc, 18,020 Landrace, and 54,254 Yorkshire sows collected from January 2001 to September 2016 from different farms in Korea were used in the analysis. Animal models and the restricted maximum likelihood method were used to estimate variances in animal genetic, permanent environmental, maternal genetic, service sire and residuals. Results The heritability estimates ranged from 0.072 to 0.102, 0.090 to 0.099, and 0.109 to 0.121 for TNB; 0.087 to 0.110, 0.088 to 0.100, and 0.099 to 0.107 for NBA; and 0.027 to 0.031, 0.050 to 0.053, and 0.073 to 0.081 for MORT in the Duroc, Landrace and Yorkshire breeds, respectively. The proportion of the total variation due to permanent environmental effects, maternal genetic effects, and service sire effects ranged from 0.042 to 0.088, 0.001 to 0.031, and 0.001 to 0.021, respectively. Spearman rank correlations among models ranged from 0.98 to 0.99, demonstrating that the maternal genetic and service sire effects have small effects on the precision of the breeding value. Conclusion Models that include additive genetic and permanent environmental effects are suitable for farrowing traits in Duroc, Landrace, and Yorkshire populations in Korea. This breed-specific variance components estimates for litter traits can be utilized for pig improvement programs in Korea.

Some variance reduction methods for numerical stochastic homogenization.

Science.gov (United States)

Blanc, X; Le Bris, C; Legoll, F

2016-04-28

We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here. © 2016 The Author(s).

The effect of oxcarbazepine in peripheral neuropathic pain depends on pain phenotype: a randomised, double-blind, placebo-controlled phenotype-stratified study

DEFF Research Database (Denmark)

Demant, Dyveke T; Lund, Karen; Vollert, Jan

2014-01-01

In neuropathic pain it has been suggested that pain phenotype based on putative pain mechanisms may predict response to treatment. This was a randomised, double-blind, placebo-controlled, and phenotype-stratified study with 2 6-week treatment periods of oxcarbazepine (1800-2400mg) and placebo...... patients: 31 with the irritable and 52 with the nonirritable nociceptor phenotype. In the total sample, oxcarbazepine relieved pain of 0.7 points (on a numeric rating scale 0-10; 95% confidence interval [CI] 0.4-1.4) more than placebo (P=0.015) and there was a significant interaction between treatment....... The primary efficacy measure was change in median pain intensity between baseline and the last week of treatment measured on an 11-point numeric rating scale, and the primary objective was to compare the effect of oxcarbazepine in patients with and without the irritable nociceptor phenotype as defined...

variance components and genetic parameters for live weight

African Journals Online (AJOL)

admin

Against this background the present study estimated the (co)variance .... Starting values for the (co)variance components of two-trait models were ..... Estimates of genetic parameters for weaning weight of beef accounting for direct-maternal.

Restricted Variance Interaction Effects

DEFF Research Database (Denmark)

Cortina, Jose M.; Köhler, Tine; Keeler, Kathleen R.

2018-01-01

Although interaction hypotheses are increasingly common in our field, many recent articles point out that authors often have difficulty justifying them. The purpose of this article is to describe a particular type of interaction: the restricted variance (RV) interaction. The essence of the RV int...

Variance Swaps in BM&F: Pricing and Viability of Hedge

Directory of Open Access Journals (Sweden)

Richard John Brostowicz Junior

2010-07-01

Full Text Available A variance swap can theoretically be priced with an infinite set of vanilla calls and puts options considering that the realized variance follows a purely diffusive process with continuous monitoring. In this article we willanalyze the possible differences in pricing considering discrete monitoring of realized variance. It will analyze the pricing of variance swaps with payoff in dollars, since there is a OTC market that works this way and thatpotentially serve as a hedge for the variance swaps traded in BM&F. Additionally, will be tested the feasibility of hedge of variance swaps when there is liquidity in just a few exercise prices, as is the case of FX optionstraded in BM&F. Thus be assembled portfolios containing variance swaps and their replicating portfolios using the available exercise prices as proposed in (DEMETERFI et al., 1999. With these portfolios, the effectiveness of the hedge was not robust in mostly of tests conducted in this work.

Secular change in 13 metabolic phenotypes: A Chinese longitudinal twin study

DEFF Research Database (Denmark)

Li, Shuxia; Pang, Zengchang; Zhang, Dongfeng

in prospective investigations. Based on Chinese twin data collected from Danish-Chinese collaboration research, we perform twin modeling on 13 metabolic phenotypes (total cholesterol; triglyceride; high density lipoprotein (HDL); low density lipoprotein (LDL); urine acid (UA); glucose; weight; body mass index...... fitted to the secular changes in each of the 13 phenotypes with best fitting model selected based on model performance. Age and sex were included as covariates in the models to adjust for their effects on secular trend. Results: Variations in secular change in 3 lipids (total cholesterol; triglyceride...

Integrating mean and variance heterogeneities to identify differentially expressed genes.

Science.gov (United States)

Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen

2016-12-06

In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment

Simultaneous Monte Carlo zero-variance estimates of several correlated means

International Nuclear Information System (INIS)

Booth, T.E.

1998-01-01

Zero-variance biasing procedures are normally associated with estimating a single mean or tally. In particular, a zero-variance solution occurs when every sampling is made proportional to the product of the true probability multiplied by the expected score (importance) subsequent to the sampling; i.e., the zero-variance sampling is importance weighted. Because every tally has a different importance function, a zero-variance biasing for one tally cannot be a zero-variance biasing for another tally (unless the tallies are perfectly correlated). The way to optimize the situation when the required tallies have positive correlation is shown

The effects of stabilizing and directional selection on phenotypic and genotypic variation in a population of RNA enzymes.

Science.gov (United States)

Hayden, Eric J; Bratulic, Sinisa; Koenig, Iwo; Ferrada, Evandro; Wagner, Andreas

2014-02-01

The distribution of variation in a quantitative trait and its underlying distribution of genotypic diversity can both be shaped by stabilizing and directional selection. Understanding either distribution is important, because it determines a population's response to natural selection. Unfortunately, existing theory makes conflicting predictions about how selection shapes these distributions, and very little pertinent experimental evidence exists. Here we study a simple genetic system, an evolving RNA enzyme (ribozyme) in which a combination of high throughput genotyping and measurement of a biochemical phenotype allow us to address this question. We show that directional selection, compared to stabilizing selection, increases the genotypic diversity of an evolving ribozyme population. In contrast, it leaves the variance in the phenotypic trait unchanged.

Identification of extreme motor phenotypes in Huntington's disease.

Science.gov (United States)

Braisch, Ulrike; Hay, Birgit; Muche, Rainer; Rothenbacher, Dietrich; Landwehrmeyer, G Bernhard; Long, Jeffrey D; Orth, Michael

2017-04-01

The manifestation of motor signs in Huntington's disease (HD) has a well-known inverse relationship with HTT CAG repeat length, but the prediction is far from perfect. The probability of finding disease modifiers is enhanced in individuals with extreme HD phenotypes. We aimed to identify extreme HD motor phenotypes conditional on CAG and age, such as patients with very early or very late onset of motor manifestation. Retrospective data were available from 1,218 healthy controls and 9,743 HD participants with CAG repeats ≥40, and a total of about 30,000 visits. Boundaries (2.5% and 97.5% quantiles) for extreme motor phenotypes (UHDRS total motor score (TMS) and motor age-at-onset) were estimated using quantile regression for longitudinal data. More than 15% of HD participants had an extreme TMS phenotype for at least one visit. In contrast, only about 4% of participants were consistent TMS extremes at two or more visits. Data from healthy controls revealed an upper cut-off of 13 for the TMS representing the extreme of motor ratings for a normal aging population. In HD, boundaries of motor age-at-onset based on diagnostic confidence or derived from the TMS data cut-off in controls were similar. In summary, a UHDRS TMS of more than 13 in an individual carrying the HD mutation indicates a high likelihood of motor manifestations of HD irrespective of CAG repeat length or age. The identification of motor phenotype extremes can be useful in the search for disease modifiers, for example, genetic or environmental such as medication. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Comparing estimates of genetic variance across different relationship models.

Science.gov (United States)

Legarra, Andres

2016-02-01

Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, Dk, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, Dk is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by Dk scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, "missing heritabilities". Copyright © 2015 Elsevier Inc. All rights reserved.

Variance estimation in the analysis of microarray data

KAUST Repository

Wang, Yuedong

2009-04-01

Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing to the small number of replications. Various methods have been proposed in the literature to overcome this lack of degrees of freedom problem. In this context, it is commonly observed that the variance increases proportionally with the intensity level, which has led many researchers to assume that the variance is a function of the mean. Here we concentrate on estimation of the variance as a function of an unknown mean in two models: the constant coefficient of variation model and the quadratic variance-mean model. Because the means are unknown and estimated with few degrees of freedom, naive methods that use the sample mean in place of the true mean are generally biased because of the errors-in-variables phenomenon. We propose three methods for overcoming this bias. The first two are variations on the theme of the so-called heteroscedastic simulation-extrapolation estimator, modified to estimate the variance function consistently. The third class of estimators is entirely different, being based on semiparametric information calculations. Simulations show the power of our methods and their lack of bias compared with the naive method that ignores the measurement error. The methodology is illustrated by using microarray data from leukaemia patients.

Variance computations for functional of absolute risk estimates.

Science.gov (United States)

Pfeiffer, R M; Petracci, E

2011-07-01

We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.

76 FR 78698 - Proposed Revocation of Permanent Variances

Science.gov (United States)

2011-12-19

... Administration (``OSHA'' or ``the Agency'') granted permanent variances to 24 companies engaged in the... DEPARTMENT OF LABOR Occupational Safety and Health Administration [Docket No. OSHA-2011-0054] Proposed Revocation of Permanent Variances AGENCY: Occupational Safety and Health Administration (OSHA...

Impact on quality culture of total quality management practices factors

Directory of Open Access Journals (Sweden)

Faihan Mosaad Saud Alotaibi

2014-09-01

Full Text Available This study investigated total quality management practices and quality culture of Saudi Arabian contractors. Improving the quality can be achieved through implementation of total quality management although studies and researches work regarding this improvement is still lacking. A quantitative approach using the survey method was employed. With assistance from the Saudi Arabia Ministry of Municipal and Rural Affairs, survey questionnaires were distributed to selected contractors in Saudi Arabia. The collected data were analysed using correlation, and multiple regression analyses. The key findings were the confirmation of significant relationships between all total quality management practices and quality culture and a positive relationship between quality management practices and quality culture. Furthermore, total quality management practices were found to be able to explain 68.1% of the variance in quality culture, while quality culture explained 12.5% of the variance in competitiveness. Quality culture was found to only partially mediate the relationship between total quality management practices and competitiveness.

Phenotypic effects of salt and heat stress over three generations in Arabidopsis thaliana.

Directory of Open Access Journals (Sweden)

Léonie Suter

Full Text Available Current and predicted environmental change will force many organisms to adapt to novel conditions, especially sessile organisms such as plants. It is therefore important to better understand how plants react to environmental stress and to what extent genotypes differ in such responses. It has been proposed that adaptation to novel conditions could be facilitated by heritable epigenetic changes induced by environmental stress, independent of genetic variation. Here we assessed phenotypic effects of heat and salt stress within and across three generations using four highly inbred Arabidopsis thaliana genotypes (Col, Cvi, Ler and Sha. Salt stress generally decreased fitness, but genotypes were differently affected, suggesting that susceptibility of A. thaliana to salt stress varies among genotypes. Heat stress at an early rosette stage had less detrimental effects but accelerated flowering in three out of four accessions. Additionally, we found three different modes of transgenerational effects on phenotypes, all harboring the potential of being adaptive: heat stress in previous generations induced faster rosette growth in Sha, both under heat and control conditions, resembling a tracking response, while in Cvi, the phenotypic variance of several traits increased, resembling diversified bet-hedging. Salt stress experienced in earlier generations altered plant architecture of Sha under salt but not control conditions, similar to transgenerational phenotypic plasticity. However, transgenerational phenotypic effects depended on the type of stress as well as on genotype, suggesting that such effects may not be a general response leading to adaptation to novel environmental conditions in A. thaliana.

Diagnostic checking in linear processes with infinit variance

OpenAIRE

Krämer, Walter; Runde, Ralf

1998-01-01

We consider empirical autocorrelations of residuals from infinite variance autoregressive processes. Unlike the finite-variance case, it emerges that the limiting distribution, after suitable normalization, is not always more concentrated around zero when residuals rather than true innovations are employed.

Genome-wide association mapping including phenotypes from relatives without genotypes in a single-step (ssGWAS for 6-week body weight in broiler chickens

Directory of Open Access Journals (Sweden)

Huiyu eWang

2014-05-01

Full Text Available The purpose of this study was to compare results obtained from various methodologies for genome-wide association studies, when applied to real data, in terms of number and commonality of regions identified and their genetic variance explained, computational speed, and possible pitfalls in interpretations of results. Methodologies include: two iteratively reweighted single-step genomic BLUP procedures (ssGWAS1 and ssGWAS2, a single-marker model (CGWAS, and BayesB. The ssGWAS methods utilize genomic breeding values (GEBVs based on combined pedigree, genomic and phenotypic information, while CGWAS and BayesB only utilize phenotypes from genotyped animals or pseudo-phenotypes. In this study, ssGWAS was performed by converting GEBVs to SNP marker effects. Unequal variances for markers were incorporated for calculating weights into a new genomic relationship matrix. SNP weights were refined iteratively. The data was body weight at 6 weeks on 274,776 broiler chickens, of which 4553 were genotyped using a 60k SNP chip. Comparison of genomic regions was based on genetic variances explained by local SNP regions (20 SNPs. After 3 iterations, the noise was greatly reduced of ssGWAS1 and results are similar to that of CGWAS, with 4 out of the top 10 regions in common. In contrast, for BayesB, the plot was dominated by a single region explaining 23.1% of the genetic variance. This same region was found by ssGWAS1 with the same rank, but the amount of genetic variation attributed to the region was only 3%. These finding emphasize the need for caution when comparing and interpreting results from various methods, and highlight that detected associations, and strength of association, strongly depends on methodologies and details of implementations. BayesB appears to overly shrink regions to zero, while overestimating the amount of genetic variation attributed to the remaining SNP effects. The real world is most likely a compromise between methods and remains to

RR-Interval variance of electrocardiogram for atrial fibrillation detection

Science.gov (United States)

Nuryani, N.; Solikhah, M.; Nugoho, A. S.; Afdala, A.; Anzihory, E.

2016-11-01

Atrial fibrillation is a serious heart problem originated from the upper chamber of the heart. The common indication of atrial fibrillation is irregularity of R peak-to-R-peak time interval, which is shortly called RR interval. The irregularity could be represented using variance or spread of RR interval. This article presents a system to detect atrial fibrillation using variances. Using clinical data of patients with atrial fibrillation attack, it is shown that the variance of electrocardiographic RR interval are higher during atrial fibrillation, compared to the normal one. Utilizing a simple detection technique and variances of RR intervals, we find a good performance of atrial fibrillation detection.

Continuous-Time Mean-Variance Portfolio Selection under the CEV Process

OpenAIRE

Ma, Hui-qiang

2014-01-01

We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV) process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance effici...

Climate change in the oceans: evolutionary versus phenotypically plastic responses of marine animals and plants.

Science.gov (United States)

Reusch, Thorsten B H

2014-01-01

I summarize marine studies on plastic versus adaptive responses to global change. Due to the lack of time series, this review focuses largely on the potential for adaptive evolution in marine animals and plants. The approaches were mainly synchronic comparisons of phenotypically divergent populations, substituting spatial contrasts in temperature or CO2 environments for temporal changes, or in assessments of adaptive genetic diversity within populations for traits important under global change. The available literature is biased towards gastropods, crustaceans, cnidarians and macroalgae. Focal traits were mostly environmental tolerances, which correspond to phenotypic buffering, a plasticity type that maintains a functional phenotype despite external disturbance. Almost all studies address coastal species that are already today exposed to fluctuations in temperature, pH and oxygen levels. Recommendations for future research include (i) initiation and analyses of observational and experimental temporal studies encompassing diverse phenotypic traits (including diapausing cues, dispersal traits, reproductive timing, morphology) (ii) quantification of nongenetic trans-generational effects along with components of additive genetic variance (iii) adaptive changes in microbe-host associations under the holobiont model in response to global change (iv) evolution of plasticity patterns under increasingly fluctuating environments and extreme conditions and (v) joint consideration of demography and evolutionary adaptation in evolutionary rescue approaches.

Variance based OFDM frame synchronization

Directory of Open Access Journals (Sweden)

Z. Fedra

2012-04-01

Full Text Available The paper deals with a new frame synchronization scheme for OFDM systems and calculates the complexity of this scheme. The scheme is based on the computing of the detection window variance. The variance is computed in two delayed times, so a modified Early-Late loop is used for the frame position detection. The proposed algorithm deals with different variants of OFDM parameters including guard interval, cyclic prefix, and has good properties regarding the choice of the algorithm's parameters since the parameters may be chosen within a wide range without having a high influence on system performance. The verification of the proposed algorithm functionality has been performed on a development environment using universal software radio peripheral (USRP hardware.

Variance, genetic control and spatial phenotypic plasticity of morphological and phenological traits in Prunus spinosa and its large fruited forms (P. x fruticans

Directory of Open Access Journals (Sweden)

Kristine Vander Mijnsbrugge

2016-11-01

Full Text Available Prunus spinosa is a highly esteemed shrub in forest and landscape plantings. Shrubs with larger organs occur often and are considered either as large fruited forms of P. spinosa or as P. x fruticans, involving a hybridization process with the ancient cultivated P. insititia (crop-to-wild gene flow. As climate change may augment hybridization processes in the future, a hybrid origin is important to detect. In addition, studying crop-to-wild gene flow can give insights in putative consequences for the wild populations. We studied the P. spinosa – P. x fruticans group, focusing on morphology and phenology in three experimental plantations. Two plantings harbored cuttings of P. spinosa (clone plantations. A third plantation comprised of a half-sib offspring from a population with both P. spinosa and P. x fruticans (family plantation. Several results point to a hybridization process as the origin of P. x fruticans. The clone plantation revealed endocarp traits to be more genetically controlled than fruit size, while this was the opposite in the family plantation, suggesting the control of fruit size being derived from the putative P. insititia parent. Bud burst, flower opening and leaf fall were genetically controlled in the clone plantation, whereas in the family plantation intrafamily variability was remarkably large for the bud burst and leaf fall, but not for the flower opening. This suggests there is a reduced genetic control for the first two phenophases, possibly caused by historic hybridization events. Pubescence on the long shoot leaves in the family plantation deviated from the short shoot leaves on the same plants and from long and short shoot leaves in the clone plantation, suggesting again a P. insititia origin. Finally, we quantified spatial phenotypic plasticity, indicating how P. spinosa may react in a changing environment. In contrast to the bud burst and leaf fall, flower opening did not demonstrate plasticity. The fruit size was

Phenotypic Stability of Energy Balance Responses to Experimental Total Sleep Deprivation and Sleep Restriction in Healthy Adults.

Science.gov (United States)

Dennis, Laura E; Spaeth, Andrea M; Goel, Namni

2016-12-19

Experimental studies have shown that sleep restriction (SR) and total sleep deprivation (TSD) produce increased caloric intake, greater fat consumption, and increased late-night eating. However, whether individuals show similar energy intake responses to both SR and TSD remains unknown. A total of N = 66 healthy adults (aged 21-50 years, 48.5% women, 72.7% African American) participated in a within-subjects laboratory protocol to compare daily and late-night intake between one night of SR (4 h time in bed, 04:00-08:00) and one night of TSD (0 h time in bed) conditions. We also examined intake responses during subsequent recovery from SR or TSD and investigated gender differences. Caloric and macronutrient intake during the day following SR and TSD were moderately to substantially consistent within individuals (Intraclass Correlation Coefficients: 0.34-0.75). During the late-night period of SR (22:00-04:00) and TSD (22:00-06:00), such consistency was slight to moderate, and participants consumed a greater percentage of calories from protein ( p = 0.01) and saturated fat ( p = 0.02) during SR, despite comparable caloric intake ( p = 0.12). Similarly, participants consumed a greater percentage of calories from saturated fat during the day following SR than TSD ( p = 0.03). Participants also consumed a greater percentage of calories from protein during recovery after TSD ( p sleep loss. This is the first evidence of phenotypic trait-like stability and differential vulnerability of energy balance responses to two commonly experienced types of sleep loss: our findings open the door for biomarker discovery and countermeasure development to predict and mitigate this critical health-related vulnerability.

Means and Variances without Calculus

Science.gov (United States)

Kinney, John J.

2005-01-01

This article gives a method of finding discrete approximations to continuous probability density functions and shows examples of its use, allowing students without calculus access to the calculation of means and variances.

Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes.

Science.gov (United States)

Cook, James P; Mahajan, Anubha; Morris, Andrew P

2017-02-01

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population stratification and relatedness through inclusion of random effects for a genetic relationship matrix. However, the utility of linear (mixed) models in the context of meta-analysis of GWAS of binary phenotypes has not been previously explored. In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework, considering designs that incorporate variable case-control imbalance, confounding factors and population stratification. Our results demonstrate that linear models can be used for meta-analysis of GWAS of binary phenotypes, without loss of power, even in the presence of extreme case-control imbalance, provided that one of the following schemes is used: (i) effective sample size weighting of Z-scores or (ii) inverse-variance weighting of allelic effect sizes after conversion onto the log-odds scale. Our conclusions thus provide essential recommendations for the development of robust protocols for meta-analysis of binary phenotypes with linear models.

Comparative UAV and Field Phenotyping to Assess Yield and Nitrogen Use Efficiency in Hybrid and Conventional Barley.

Science.gov (United States)

Kefauver, Shawn C; Vicente, Rubén; Vergara-Díaz, Omar; Fernandez-Gallego, Jose A; Kerfal, Samir; Lopez, Antonio; Melichar, James P E; Serret Molins, María D; Araus, José L

2017-01-01

With the commercialization and increasing availability of Unmanned Aerial Vehicles (UAVs) multiple rotor copters have expanded rapidly in plant phenotyping studies with their ability to provide clear, high resolution images. As such, the traditional bottleneck of plant phenotyping has shifted from data collection to data processing. Fortunately, the necessarily controlled and repetitive design of plant phenotyping allows for the development of semi-automatic computer processing tools that may sufficiently reduce the time spent in data extraction. Here we present a comparison of UAV and field based high throughput plant phenotyping (HTPP) using the free, open-source image analysis software FIJI (Fiji is just ImageJ) using RGB (conventional digital cameras), multispectral and thermal aerial imagery in combination with a matching suite of ground sensors in a study of two hybrids and one conventional barely variety with ten different nitrogen treatments, combining different fertilization levels and application schedules. A detailed correlation network for physiological traits and exploration of the data comparing between treatments and varieties provided insights into crop performance under different management scenarios. Multivariate regression models explained 77.8, 71.6, and 82.7% of the variance in yield from aerial, ground, and combined data sets, respectively.

Beyond the Mean: Sensitivities of the Variance of Population Growth.

Science.gov (United States)

Trotter, Meredith V; Krishna-Kumar, Siddharth; Tuljapurkar, Shripad

2013-03-01

Populations in variable environments are described by both a mean growth rate and a variance of stochastic population growth. Increasing variance will increase the width of confidence bounds around estimates of population size, growth, probability of and time to quasi-extinction. However, traditional sensitivity analyses of stochastic matrix models only consider the sensitivity of the mean growth rate. We derive an exact method for calculating the sensitivity of the variance in population growth to changes in demographic parameters. Sensitivities of the variance also allow a new sensitivity calculation for the cumulative probability of quasi-extinction. We apply this new analysis tool to an empirical dataset on at-risk polar bears to demonstrate its utility in conservation biology We find that in many cases a change in life history parameters will increase both the mean and variance of population growth of polar bears. This counterintuitive behaviour of the variance complicates predictions about overall population impacts of management interventions. Sensitivity calculations for cumulative extinction risk factor in changes to both mean and variance, providing a highly useful quantitative tool for conservation management. The mean stochastic growth rate and its sensitivities do not fully describe the dynamics of population growth. The use of variance sensitivities gives a more complete understanding of population dynamics and facilitates the calculation of new sensitivities for extinction processes.

Evaluation of Mean and Variance Integrals without Integration

Science.gov (United States)

Joarder, A. H.; Omar, M. H.

2007-01-01

The mean and variance of some continuous distributions, in particular the exponentially decreasing probability distribution and the normal distribution, are considered. Since they involve integration by parts, many students do not feel comfortable. In this note, a technique is demonstrated for deriving mean and variance through differential…

Approximate zero-variance Monte Carlo estimation of Markovian unreliability

International Nuclear Information System (INIS)

Delcoux, J.L.; Labeau, P.E.; Devooght, J.

1997-01-01

Monte Carlo simulation has become an important tool for the estimation of reliability characteristics, since conventional numerical methods are no more efficient when the size of the system to solve increases. However, evaluating by a simulation the probability of occurrence of very rare events means playing a very large number of histories of the system, which leads to unacceptable computation times. Acceleration and variance reduction techniques have to be worked out. We show in this paper how to write the equations of Markovian reliability as a transport problem, and how the well known zero-variance scheme can be adapted to this application. But such a method is always specific to the estimation of one quality, while a Monte Carlo simulation allows to perform simultaneously estimations of diverse quantities. Therefore, the estimation of one of them could be made more accurate while degrading at the same time the variance of other estimations. We propound here a method to reduce simultaneously the variance for several quantities, by using probability laws that would lead to zero-variance in the estimation of a mean of these quantities. Just like the zero-variance one, the method we propound is impossible to perform exactly. However, we show that simple approximations of it may be very efficient. (author)

Variable phenotypic expression and onset in MYH14 distal hereditary motor neuropathy phenotype in a large, multigenerational North American family.

Science.gov (United States)

Iyadurai, Stanley; Arnold, W David; Kissel, John T; Ruhno, Corey; Mcgovern, Vicki L; Snyder, Pamela J; Prior, Thomas W; Roggenbuck, Jennifer; Burghes, Arthur H; Kolb, Stephen J

2017-08-01

Distal hereditary motor neuropathy (dHMN) causes distal-predominant weakness without prominent sensory loss. Myosin heavy chain disorders most commonly result in distal myopathy and cardiomyopathy with or without hearing loss, but a complex phenotype with dHMN, myopathy, hoarseness, and hearing loss was reported in a Korean family with a c.2822G>T mutation in MYH14. In this study we report phenotypic features in a North American family with the c.2822G>T in MYH14. Clinical and molecular characterization was performed in a large, 6-generation, Caucasian family with MYH14 dHMN. A total of 11 affected and 7 unaffected individuals were evaluated and showed varying age of onset and severity of weakness. Genotypic concordance was confirmed with molecular analysis. Electrophysiological studies demonstrated distal motor axonal degeneration without myopathy in all affected subjects tested. Mutation of MYH14 can result in a range of neuromuscular phenotypes that includes a dHMN and hearing loss phenotype with variable age of onset. Muscle Nerve 56: 341-345, 2017. © 2016 Wiley Periodicals, Inc.

Variance in binary stellar population synthesis

Science.gov (United States)

Breivik, Katelyn; Larson, Shane L.

2016-03-01

In the years preceding LISA, Milky Way compact binary population simulations can be used to inform the science capabilities of the mission. Galactic population simulation efforts generally focus on high fidelity models that require extensive computational power to produce a single simulated population for each model. Each simulated population represents an incomplete sample of the functions governing compact binary evolution, thus introducing variance from one simulation to another. We present a rapid Monte Carlo population simulation technique that can simulate thousands of populations in less than a week, thus allowing a full exploration of the variance associated with a binary stellar evolution model.

Correction for Measurement Error from Genotyping-by-Sequencing in Genomic Variance and Genomic Prediction Models

DEFF Research Database (Denmark)

Ashraf, Bilal; Janss, Luc; Jensen, Just

sample). The GBSeq data can be used directly in genomic models in the form of individual SNP allele-frequency estimates (e.g., reference reads/total reads per polymorphic site per individual), but is subject to measurement error due to the low sequencing depth per individual. Due to technical reasons....... In the current work we show how the correction for measurement error in GBSeq can also be applied in whole genome genomic variance and genomic prediction models. Bayesian whole-genome random regression models are proposed to allow implementation of large-scale SNP-based models with a per-SNP correction...... for measurement error. We show correct retrieval of genomic explained variance, and improved genomic prediction when accounting for the measurement error in GBSeq data...

Genetic diversity assessment of sesame core collection in China by phenotype and molecular markers and extraction of a mini-core collection

Directory of Open Access Journals (Sweden)

Zhang Yanxin

2012-11-01

Full Text Available Abstract Background Sesame (Sesamum indicum L. is one of the four major oil crops in China. A sesame core collection (CC was established in China in 2000, but no complete study on its genetic diversity has been carried out at either the phenotypic or molecular level. To provide technical guidance, a theoretical basis for further collection, effective protection, reasonable application, and a complete analysis of sesame genetic resources, a genetic diversity assessment of the sesame CC in China was conducted using phenotypic and molecular data and by extracting a sesame mini-core collection (MC. Results Results from a genetic diversity assessment of sesame CC in China were significantly inconsistent at the phenotypic and molecular levels. A Mantel test revealed the insignificant correlation between phenotype and molecular marker information (r = 0.0043, t = 0.1320, P = 0.5525. The Shannon-Weaver diversity index (I and Nei genetic diversity index (h were higher (I = 0.9537, h = 0.5490 when calculated using phenotypic data from the CC than when using molecular data (I = 0.3467, h = 0.2218. A mini-core collection (MC containing 184 accessions was extracted based on both phenotypic and molecular data, with a low mean difference percentage (MD, 1.64%, low variance difference percentage (VD, 22.58%, large variable rate of coefficient of variance (VR, 114.86%, and large coincidence rate of range (CR, 95.76%. For molecular data, the diversity indices and the polymorphism information content (PIC for the MC were significantly higher than for the CC. Compared to an alternative random sampling strategy, the advantages of capturing genetic diversity and validation by extracting a MC using an advanced maximization strategy were proven. Conclusions This study provides a comprehensive characterization of the phenotypic and molecular genetic diversities of the sesame CC in China. A MC was extracted using both phenotypic and molecular data. Low MD% and VD%, and

Genetic diversity assessment of sesame core collection in China by phenotype and molecular markers and extraction of a mini-core collection

Science.gov (United States)

2012-01-01

Background Sesame (Sesamum indicum L.) is one of the four major oil crops in China. A sesame core collection (CC) was established in China in 2000, but no complete study on its genetic diversity has been carried out at either the phenotypic or molecular level. To provide technical guidance, a theoretical basis for further collection, effective protection, reasonable application, and a complete analysis of sesame genetic resources, a genetic diversity assessment of the sesame CC in China was conducted using phenotypic and molecular data and by extracting a sesame mini-core collection (MC). Results Results from a genetic diversity assessment of sesame CC in China were significantly inconsistent at the phenotypic and molecular levels. A Mantel test revealed the insignificant correlation between phenotype and molecular marker information (r = 0.0043, t = 0.1320, P = 0.5525). The Shannon-Weaver diversity index (I) and Nei genetic diversity index (h) were higher (I = 0.9537, h = 0.5490) when calculated using phenotypic data from the CC than when using molecular data (I = 0.3467, h = 0.2218). A mini-core collection (MC) containing 184 accessions was extracted based on both phenotypic and molecular data, with a low mean difference percentage (MD, 1.64%), low variance difference percentage (VD, 22.58%), large variable rate of coefficient of variance (VR, 114.86%), and large coincidence rate of range (CR, 95.76%). For molecular data, the diversity indices and the polymorphism information content (PIC) for the MC were significantly higher than for the CC. Compared to an alternative random sampling strategy, the advantages of capturing genetic diversity and validation by extracting a MC using an advanced maximization strategy were proven. Conclusions This study provides a comprehensive characterization of the phenotypic and molecular genetic diversities of the sesame CC in China. A MC was extracted using both phenotypic and molecular data. Low MD% and VD%, and large VR% and CR

A Mean variance analysis of arbitrage portfolios

Science.gov (United States)

Fang, Shuhong

2007-03-01

Based on the careful analysis of the definition of arbitrage portfolio and its return, the author presents a mean-variance analysis of the return of arbitrage portfolios, which implies that Korkie and Turtle's results ( B. Korkie, H.J. Turtle, A mean-variance analysis of self-financing portfolios, Manage. Sci. 48 (2002) 427-443) are misleading. A practical example is given to show the difference between the arbitrage portfolio frontier and the usual portfolio frontier.

Mean-Variance Optimization in Markov Decision Processes

OpenAIRE

Mannor, Shie; Tsitsiklis, John N.

2011-01-01

We consider finite horizon Markov decision processes under performance measures that involve both the mean and the variance of the cumulative reward. We show that either randomized or history-based policies can improve performance. We prove that the complexity of computing a policy that maximizes the mean reward under a variance constraint is NP-hard for some cases, and strongly NP-hard for others. We finally offer pseudo-polynomial exact and approximation algorithms.

Capturing Option Anomalies with a Variance-Dependent Pricing Kernel

DEFF Research Database (Denmark)

Christoffersen, Peter; Heston, Steven; Jacobs, Kris

2013-01-01

We develop a GARCH option model with a new pricing kernel allowing for a variance premium. While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is nonmonotonic. A negative variance premium makes it U shaped. We present new semiparametric...... evidence to confirm this U-shaped relationship between the risk-neutral and physical probability densities. The new pricing kernel substantially improves our ability to reconcile the time-series properties of stock returns with the cross-section of option prices. It provides a unified explanation...... for the implied volatility puzzle, the overreaction of long-term options to changes in short-term variance, and the fat tails of the risk-neutral return distribution relative to the physical distribution....

Gender Variance and Educational Psychology: Implications for Practice

Science.gov (United States)

Yavuz, Carrie

2016-01-01

The area of gender variance appears to be more visible in both the media and everyday life. Within educational psychology literature gender variance remains underrepresented. The positioning of educational psychologists working across the three levels of child and family, school or establishment and education authority/council, means that they are…

Demonstration of a zero-variance based scheme for variance reduction to a mini-core Monte Carlo calculation

Energy Technology Data Exchange (ETDEWEB)

Christoforou, Stavros, E-mail: stavros.christoforou@gmail.com [Kirinthou 17, 34100, Chalkida (Greece); Hoogenboom, J. Eduard, E-mail: j.e.hoogenboom@tudelft.nl [Department of Applied Sciences, Delft University of Technology (Netherlands)

2011-07-01

A zero-variance based scheme is implemented and tested in the MCNP5 Monte Carlo code. The scheme is applied to a mini-core reactor using the adjoint function obtained from a deterministic calculation for biasing the transport kernels. It is demonstrated that the variance of the k{sub eff} estimate is halved compared to a standard criticality calculation. In addition, the biasing does not affect source distribution convergence of the system. However, since the code lacked optimisations for speed, we were not able to demonstrate an appropriate increase in the efficiency of the calculation, because of the higher CPU time cost. (author)

Variance-in-Mean Effects of the Long Forward-Rate Slope

DEFF Research Database (Denmark)

Christiansen, Charlotte

2005-01-01

This paper contains an empirical analysis of the dependence of the long forward-rate slope on the long-rate variance. The long forward-rate slope and the long rate are described by a bivariate GARCH-in-mean model. In accordance with theory, a negative long-rate variance-in-mean effect for the long...... forward-rate slope is documented. Thus, the greater the long-rate variance, the steeper the long forward-rate curve slopes downward (the long forward-rate slope is negative). The variance-in-mean effect is both statistically and economically significant....

Variance-based sensitivity indices for models with dependent inputs

International Nuclear Information System (INIS)

Mara, Thierry A.; Tarantola, Stefano

2012-01-01

Computational models are intensively used in engineering for risk analysis or prediction of future outcomes. Uncertainty and sensitivity analyses are of great help in these purposes. Although several methods exist to perform variance-based sensitivity analysis of model output with independent inputs only a few are proposed in the literature in the case of dependent inputs. This is explained by the fact that the theoretical framework for the independent case is set and a univocal set of variance-based sensitivity indices is defined. In the present work, we propose a set of variance-based sensitivity indices to perform sensitivity analysis of models with dependent inputs. These measures allow us to distinguish between the mutual dependent contribution and the independent contribution of an input to the model response variance. Their definition relies on a specific orthogonalisation of the inputs and ANOVA-representations of the model output. In the applications, we show the interest of the new sensitivity indices for model simplification setting. - Highlights: ► Uncertainty and sensitivity analyses are of great help in engineering. ► Several methods exist to perform variance-based sensitivity analysis of model output with independent inputs. ► We define a set of variance-based sensitivity indices for models with dependent inputs. ► Inputs mutual contributions are distinguished from their independent contributions. ► Analytical and computational tests are performed and discussed.

Simultaneous Monte Carlo zero-variance estimates of several correlated means

International Nuclear Information System (INIS)

Booth, T.E.

1997-08-01

Zero variance procedures have been in existence since the dawn of Monte Carlo. Previous works all treat the problem of zero variance solutions for a single tally. One often wants to get low variance solutions to more than one tally. When the sets of random walks needed for two tallies are similar, it is more efficient to do zero variance biasing for both tallies in the same Monte Carlo run, instead of two separate runs. The theory presented here correlates the random walks of particles by the similarity of their tallies. Particles with dissimilar tallies rapidly become uncorrelated whereas particles with similar tallies will stay correlated through most of their random walk. The theory herein should allow practitioners to make efficient use of zero-variance biasing procedures in practical problems

Factors in Early Adolescence Associated With a Mole-Prone Phenotype in Late Adolescence.

Science.gov (United States)

Xu, Haoming; Marchetti, Michael A; Dusza, Stephen W; Chung, Esther; Fonseca, Maira; Scope, Alon; Geller, Alan C; Bishop, Marilyn; Marghoob, Ashfaq A; Halpern, Allan C

2017-10-01

Nevi are important phenotypic risk factors for melanoma in adults. Few studies have examined the constitutional and behavioral factors associated with a mole-prone phenotype in adolescents. To identify host, behavioral, and dermoscopic factors in early adolescence (age, 14 years) that are associated with a mole-prone phenotype in late adolescence (age, 17 years). A prospective observational cohort study from the Study of Nevi in Children was conducted from January 1, 2009, to December 31, 2014, with a 2- to 3-year follow-up. A total of 569 students from the school system in Framingham, Massachusetts, were enrolled in the 8th or 9th grade (baseline; mean [SD] age, 14.4 [0.7] years). The overall retention rate was 73.3%, and 417 students were reassessed in the 11th grade. Mole-prone phenotype in the 11th grade, defined as total nevus count of the back and 1 randomly selected leg in the top decile of the cohort or having any nevi greater than 5 mm in diameter. Of the 417 students assessed at follow-up in the 11th grade (166 females and 251 males; mean [SD] age, 17.0 [0.4] years), 111 participants (26.6%) demonstrated a mole-prone phenotype: 69 students (62.2%) with 1 nevus greater than 5 mm in diameter, 23 students (20.7%) with total nevus count in the top decile, and 19 students (17.1%) with both characteristics. On multivariate analysis, baseline total nevus count (adjusted odds ratio, 9.08; 95% CI, 4.0-23.7; P adolescents for higher-intensity counseling about sun protection and skin self-examination.

Variance swap payoffs, risk premia and extreme market conditions

DEFF Research Database (Denmark)

Rombouts, Jeroen V.K.; Stentoft, Lars; Violante, Francesco

This paper estimates the Variance Risk Premium (VRP) directly from synthetic variance swap payoffs. Since variance swap payoffs are highly volatile, we extract the VRP by using signal extraction techniques based on a state-space representation of our model in combination with a simple economic....... The latter variables and the VRP generate different return predictability on the major US indices. A factor model is proposed to extract a market VRP which turns out to be priced when considering Fama and French portfolios....

Estimating quadratic variation using realized variance

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Shephard, N.

2002-01-01

with a rather general SV model - which is a special case of the semimartingale model. Then QV is integrated variance and we can derive the asymptotic distribution of the RV and its rate of convergence. These results do not require us to specify a model for either the drift or volatility functions, although we...... have to impose some weak regularity assumptions. We illustrate the use of the limit theory on some exchange rate data and some stock data. We show that even with large values of M the RV is sometimes a quite noisy estimator of integrated variance. Copyright © 2002 John Wiley & Sons, Ltd....

Dynamics of Variance Risk Premia, Investors' Sentiment and Return Predictability

DEFF Research Database (Denmark)

Rombouts, Jerome V.K.; Stentoft, Lars; Violante, Francesco

We develop a joint framework linking the physical variance and its risk neutral expectation implying variance risk premia that are persistent, appropriately reacting to changes in level and variability of the variance and naturally satisfying the sign constraint. Using option market data and real...... events and only marginally by the premium associated with normal price fluctuations....

A note on minimum-variance theory and beyond

Energy Technology Data Exchange (ETDEWEB)

Feng Jianfeng [Department of Informatics, Sussex University, Brighton, BN1 9QH (United Kingdom); Tartaglia, Giangaetano [Physics Department, Rome University ' La Sapienza' , Rome 00185 (Italy); Tirozzi, Brunello [Physics Department, Rome University ' La Sapienza' , Rome 00185 (Italy)

2004-04-30

We revisit the minimum-variance theory proposed by Harris and Wolpert (1998 Nature 394 780-4), discuss the implications of the theory on modelling the firing patterns of single neurons and analytically find the optimal control signals, trajectories and velocities. Under the rate coding assumption, input control signals employed in the minimum-variance theory should be Fitts processes rather than Poisson processes. Only if information is coded by interspike intervals, Poisson processes are in agreement with the inputs employed in the minimum-variance theory. For the integrate-and-fire model with Fitts process inputs, interspike intervals of efferent spike trains are very irregular. We introduce diffusion approximations to approximate neural models with renewal process inputs and present theoretical results on calculating moments of interspike intervals of the integrate-and-fire model. Results in Feng, et al (2002 J. Phys. A: Math. Gen. 35 7287-304) are generalized. In conclusion, we present a complete picture on the minimum-variance theory ranging from input control signals, to model outputs, and to its implications on modelling firing patterns of single neurons.

A note on minimum-variance theory and beyond

International Nuclear Information System (INIS)

Feng Jianfeng; Tartaglia, Giangaetano; Tirozzi, Brunello

2004-01-01

We revisit the minimum-variance theory proposed by Harris and Wolpert (1998 Nature 394 780-4), discuss the implications of the theory on modelling the firing patterns of single neurons and analytically find the optimal control signals, trajectories and velocities. Under the rate coding assumption, input control signals employed in the minimum-variance theory should be Fitts processes rather than Poisson processes. Only if information is coded by interspike intervals, Poisson processes are in agreement with the inputs employed in the minimum-variance theory. For the integrate-and-fire model with Fitts process inputs, interspike intervals of efferent spike trains are very irregular. We introduce diffusion approximations to approximate neural models with renewal process inputs and present theoretical results on calculating moments of interspike intervals of the integrate-and-fire model. Results in Feng, et al (2002 J. Phys. A: Math. Gen. 35 7287-304) are generalized. In conclusion, we present a complete picture on the minimum-variance theory ranging from input control signals, to model outputs, and to its implications on modelling firing patterns of single neurons

Phenotypic Stability of Energy Balance Responses to Experimental Total Sleep Deprivation and Sleep Restriction in Healthy Adults

Directory of Open Access Journals (Sweden)

Laura E. Dennis

2016-12-01

Full Text Available Experimental studies have shown that sleep restriction (SR and total sleep deprivation (TSD produce increased caloric intake, greater fat consumption, and increased late-night eating. However, whether individuals show similar energy intake responses to both SR and TSD remains unknown. A total of N = 66 healthy adults (aged 21–50 years, 48.5% women, 72.7% African American participated in a within-subjects laboratory protocol to compare daily and late-night intake between one night of SR (4 h time in bed, 04:00–08:00 and one night of TSD (0 h time in bed conditions. We also examined intake responses during subsequent recovery from SR or TSD and investigated gender differences. Caloric and macronutrient intake during the day following SR and TSD were moderately to substantially consistent within individuals (Intraclass Correlation Coefficients: 0.34–0.75. During the late-night period of SR (22:00–04:00 and TSD (22:00–06:00, such consistency was slight to moderate, and participants consumed a greater percentage of calories from protein (p = 0.01 and saturated fat (p = 0.02 during SR, despite comparable caloric intake (p = 0.12. Similarly, participants consumed a greater percentage of calories from saturated fat during the day following SR than TSD (p = 0.03. Participants also consumed a greater percentage of calories from protein during recovery after TSD (p < 0.001. Caloric intake was greater in men during late-night hours and the day following sleep loss. This is the first evidence of phenotypic trait-like stability and differential vulnerability of energy balance responses to two commonly experienced types of sleep loss: our findings open the door for biomarker discovery and countermeasure development to predict and mitigate this critical health-related vulnerability.

Metabolic syndrome and metabolic risk profile according to polycystic ovary syndrome phenotype.

Science.gov (United States)

Bil, Enes; Dilbaz, Berna; Cirik, Derya Akdag; Ozelci, Runa; Ozkaya, Enis; Dilbaz, Serdar

2016-07-01

It is unknown which phenotype of polycystic ovary syndrome (PCOS) has a greater metabolic risk and how to detect this risk. The aim of this study was therefore to compare the incidence of metabolic syndrome (MetS) and metabolic risk profile (MRP) for different phenotypes. A total of 100 consecutive newly diagnosed PCOS women in a tertiary referral hospital were recruited. Patients were classified into four phenotypes according to the Rotterdam criteria, on the presence of at least two of the three criteria hyperandrogenism (H), oligo/anovulation (O) and PCO appearance (P): phenotype A, H + O + P; phenotype B, H + O; phenotype C, H + P; phenotype D, O + P. Prevalence of MetS and MRP were compared among the four groups. Based on Natural Cholesterol Education Program Adult Treatment Panel III diagnostic criteria, MetS prevalence was higher in phenotypes A and B (29.6% and 34.5%) compared with the other phenotypes (10.0% and 8.3%; P 3.8 was significantly higher in androgenic PCOS phenotypes. After logistic regression analysis, visceral adiposity index (VAI) was the only independent predictor of MetS in PCOS (P = 0.002). VAI was also significantly higher in phenotype B, when compared with the others (P risk of MetS among the four phenotypes, and VAI may be a predictor of metabolic risk in PCOS women. © 2016 Japan Society of Obstetrics and Gynecology.

Estimating High-Frequency Based (Co-) Variances: A Unified Approach

DEFF Research Database (Denmark)

Voev, Valeri; Nolte, Ingmar

We propose a unified framework for estimating integrated variances and covariances based on simple OLS regressions, allowing for a general market microstructure noise specification. We show that our estimators can outperform, in terms of the root mean squared error criterion, the most recent...... and commonly applied estimators, such as the realized kernels of Barndorff-Nielsen, Hansen, Lunde & Shephard (2006), the two-scales realized variance of Zhang, Mykland & Aït-Sahalia (2005), the Hayashi & Yoshida (2005) covariance estimator, and the realized variance and covariance with the optimal sampling...

Demonstration of a zero-variance based scheme for variance reduction to a mini-core Monte Carlo calculation

International Nuclear Information System (INIS)

Christoforou, Stavros; Hoogenboom, J. Eduard

2011-01-01

A zero-variance based scheme is implemented and tested in the MCNP5 Monte Carlo code. The scheme is applied to a mini-core reactor using the adjoint function obtained from a deterministic calculation for biasing the transport kernels. It is demonstrated that the variance of the k_e_f_f estimate is halved compared to a standard criticality calculation. In addition, the biasing does not affect source distribution convergence of the system. However, since the code lacked optimisations for speed, we were not able to demonstrate an appropriate increase in the efficiency of the calculation, because of the higher CPU time cost. (author)

CT reconstruction from few-views with anisotropic edge-guided total variance

International Nuclear Information System (INIS)

Rong, Junyan; Liu, Wenlei; Gao, Peng; Liao, Qimei; Jiao, Chun; Ma, Jianhua; Lu, Hongbing

2016-01-01

To overcome the oversmoothing drawback in the edge areas when reconstructing few-view CT with total variation (TV) minimization, in this paper, we propose an anisotropic edge-guided TV minimization framework for few-view CT reconstruction. In the framework, anisotropic TV is summed with pre-weighted image gradient and then used as the object function for minimizing. It includes edge-guided TV minimization (EGTV) and edge-guided adaptive-weighted TV minimization (EGAwTV) algorithms. For EGTV algorithm, the weights of the TV discretization term are updated by anisotropic edge information detected from the image, whereas the weights for EGAwTV are determined based on edge information and local image-intensity gradients. To solve the minimization problem of the proposed algorithm, a similar TV-based minimization implementation is developed to address the raw data fidelity and other constraints. The evaluation results using both computer simulations with the Shepp-Logan phantom and experimental data from a physical phantom demonstrate that the proposed algorithms exhibit noticeable gains in the merits of spatial resolution compared with the conventional TV and other modified TV algorithms.

Presbycusis phenotypes form a heterogeneous continuum when ordered by degree and configuration of hearing loss.

Science.gov (United States)

Allen, Paul D; Eddins, David A

2010-06-01

Many reports have documented age-by-frequency increases in average auditory thresholds in various human populations. Despite this, the prevalence of different patterns of hearing loss in presbycusis remains uncertain. We examined 'presbycusis phenotypes' in a database of 960 subjects (552 female, 408 male, 18-92 years) that each had 30 measures of peripheral hearing sensitivity: pure tone audiograms for left and right ears from 0.25 to 8 kHz and DPOAE for each ear with F(mean)=1-6.4 kHz. Surprisingly, the hearing phenotypes did not naturally separate into discrete classes of presbycusis. Principal component (PC) analysis revealed that two principal components account for 74% of the variance among the 30 measures of hearing. The two components represent the overall degree (PC1) and configuration of loss (Flat vs. Sloping; PC2) and the phenotypes form a continuum when plotted against them. A heuristic partitioning of this continuum produced classes of presbycusis that vary in their degree of Sloping or Flat hearing loss, suggesting that the previously reported sub-types of presbycusis arise from the categorical segregation of a continuous and heterogeneous distribution. Further, most phenotypes lie intermediate to the extremes of either Flat or Sloping loss, indicating that if audiometric configuration does predict presbycusis etiology, then a mixed origin is the most prevalent. Copyright 2010 Elsevier B.V. All rights reserved.

Technical Note: On the efficiency of variance reduction techniques for Monte Carlo estimates of imaging noise.

Science.gov (United States)

Sharma, Diksha; Sempau, Josep; Badano, Aldo

2018-02-01

Monte Carlo simulations require large number of histories to obtain reliable estimates of the quantity of interest and its associated statistical uncertainty. Numerous variance reduction techniques (VRTs) have been employed to increase computational efficiency by reducing the statistical uncertainty. We investigate the effect of two VRTs for optical transport methods on accuracy and computing time for the estimation of variance (noise) in x-ray imaging detectors. We describe two VRTs. In the first, we preferentially alter the direction of the optical photons to increase detection probability. In the second, we follow only a fraction of the total optical photons generated. In both techniques, the statistical weight of photons is altered to maintain the signal mean. We use fastdetect2, an open-source, freely available optical transport routine from the hybridmantis package. We simulate VRTs for a variety of detector models and energy sources. The imaging data from the VRT simulations are then compared to the analog case (no VRT) using pulse height spectra, Swank factor, and the variance of the Swank estimate. We analyze the effect of VRTs on the statistical uncertainty associated with Swank factors. VRTs increased the relative efficiency by as much as a factor of 9. We demonstrate that we can achieve the same variance of the Swank factor with less computing time. With this approach, the simulations can be stopped when the variance of the variance estimates reaches the desired level of uncertainty. We implemented analytic estimates of the variance of Swank factor and demonstrated the effect of VRTs on image quality calculations. Our findings indicate that the Swank factor is dominated by the x-ray interaction profile as compared to the additional uncertainty introduced in the optical transport by the use of VRTs. For simulation experiments that aim at reducing the uncertainty in the Swank factor estimate, any of the proposed VRT can be used for increasing the relative

The Genealogical Consequences of Fecundity Variance Polymorphism

Science.gov (United States)

Taylor, Jesse E.

2009-01-01

The genealogical consequences of within-generation fecundity variance polymorphism are studied using coalescent processes structured by genetic backgrounds. I show that these processes have three distinctive features. The first is that the coalescent rates within backgrounds are not jointly proportional to the infinitesimal variance, but instead depend only on the frequencies and traits of genotypes containing each allele. Second, the coalescent processes at unlinked loci are correlated with the genealogy at the selected locus; i.e., fecundity variance polymorphism has a genomewide impact on genealogies. Third, in diploid models, there are infinitely many combinations of fecundity distributions that have the same diffusion approximation but distinct coalescent processes; i.e., in this class of models, ancestral processes and allele frequency dynamics are not in one-to-one correspondence. Similar properties are expected to hold in models that allow for heritable variation in other traits that affect the coalescent effective population size, such as sex ratio or fecundity and survival schedules. PMID:19433628

Phenotypic plasticity and local adaptation in leaf ecophysiological traits of 13 contrasting cork oak populations under different water availabilities.

Science.gov (United States)

Ramírez-Valiente, Jose Alberto; Sánchez-Gómez, David; Aranda, Ismael; Valladares, Fernando

2010-05-01

Plants distributed across a wide range of environmental conditions are submitted to differential selective pressures. Long-term selection can lead to the development of adaptations to the local environment, generating ecotypic differentiation. Additionally, plant species can cope with this environmental variability by phenotypic plasticity. In this study, we examine the importance of both processes in coping with environmental heterogeneity in the Mediterranean sclerophyllous cork oak Quercus suber. For this purpose, we measured growth and key functional traits at the leaf level in 9-year-old plants across 2 years of contrasting precipitation (2005 and 2006) in a common garden. Plants were grown from acorns originated from 13 populations spanning a wide range of climates along the distribution range of the species. The traits measured were: leaf size (LS), specific leaf area (SLA), carbon isotope discrimination (Delta(13)C) and leaf nitrogen content per unit mass (N(mass)). Inter-population differences in LS, SLA and Delta(13)C were found. These differences were associated with rainfall and temperature at the sites of origin, suggesting local adaptation in response to diverging climates. Additionally, SLA and LS exhibited positive responses to the increase in annual rainfall. Year effect explained 28% of the total phenotypic variance in LS and 2.7% in SLA. There was a significant genotype x environment interaction for shoot growth and a phenotypic correlation between the difference in shoot growth among years and the annual mean temperature at origin. This suggests that populations originating from warm sites can benefit more from wet conditions than populations from cool sites. Finally, we investigated the relationships between functional traits and aboveground growth by several regression models. Our results showed that plants with lower SLA presented larger aboveground growth in a dry year and plants with larger leaf sizes displayed larger growth rates in both

On Mean-Variance Analysis

OpenAIRE

Li, Yang; Pirvu, Traian A

2011-01-01

This paper considers the mean variance portfolio management problem. We examine portfolios which contain both primary and derivative securities. The challenge in this context is due to portfolio's nonlinearities. The delta-gamma approximation is employed to overcome it. Thus, the optimization problem is reduced to a well posed quadratic program. The methodology developed in this paper can be also applied to pricing and hedging in incomplete markets.

Comparative UAV and Field Phenotyping to Assess Yield and Nitrogen Use Efficiency in Hybrid and Conventional Barley

Directory of Open Access Journals (Sweden)

Shawn C. Kefauver

2017-10-01

Full Text Available With the commercialization and increasing availability of Unmanned Aerial Vehicles (UAVs multiple rotor copters have expanded rapidly in plant phenotyping studies with their ability to provide clear, high resolution images. As such, the traditional bottleneck of plant phenotyping has shifted from data collection to data processing. Fortunately, the necessarily controlled and repetitive design of plant phenotyping allows for the development of semi-automatic computer processing tools that may sufficiently reduce the time spent in data extraction. Here we present a comparison of UAV and field based high throughput plant phenotyping (HTPP using the free, open-source image analysis software FIJI (Fiji is just ImageJ using RGB (conventional digital cameras, multispectral and thermal aerial imagery in combination with a matching suite of ground sensors in a study of two hybrids and one conventional barely variety with ten different nitrogen treatments, combining different fertilization levels and application schedules. A detailed correlation network for physiological traits and exploration of the data comparing between treatments and varieties provided insights into crop performance under different management scenarios. Multivariate regression models explained 77.8, 71.6, and 82.7% of the variance in yield from aerial, ground, and combined data sets, respectively.

Modelling volatility by variance decomposition

DEFF Research Database (Denmark)

Amado, Cristina; Teräsvirta, Timo

In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the variance of the model to have a smooth time-varying structure of either additive or multiplicative type. The suggested parameterisations describe both nonlinearity and structural change in the condit...

Genetic Variance in Homophobia: Evidence from Self- and Peer Reports.

Science.gov (United States)

Zapko-Willmes, Alexandra; Kandler, Christian

2018-01-01

The present twin study combined self- and peer assessments of twins' general homophobia targeting gay men in order to replicate previous behavior genetic findings across different rater perspectives and to disentangle self-rater-specific variance from common variance in self- and peer-reported homophobia (i.e., rater-consistent variance). We hypothesized rater-consistent variance in homophobia to be attributable to genetic and nonshared environmental effects, and self-rater-specific variance to be partially accounted for by genetic influences. A sample of 869 twins and 1329 peer raters completed a seven item scale containing cognitive, affective, and discriminatory homophobic tendencies. After correction for age and sex differences, we found most of the genetic contributions (62%) and significant nonshared environmental contributions (16%) to individual differences in self-reports on homophobia to be also reflected in peer-reported homophobia. A significant genetic component, however, was self-report-specific (38%), suggesting that self-assessments alone produce inflated heritability estimates to some degree. Different explanations are discussed.

Decomposition of Variance for Spatial Cox Processes.

Science.gov (United States)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

2013-03-01

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive or log linear random intensity functions. We moreover consider a new and flexible class of pair correlation function models given in terms of normal variance mixture covariance functions. The proposed methodology is applied to point pattern data sets of locations of tropical rain forest trees.

Grammatical and lexical variance in English

CERN Document Server

Quirk, Randolph

2014-01-01

Written by one of Britain's most distinguished linguists, this book is concerned with the phenomenon of variance in English grammar and vocabulary across regional, social, stylistic and temporal space.

Variance decomposition in stochastic simulators.

Science.gov (United States)

Le Maître, O P; Knio, O M; Moraes, A

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

Science.gov (United States)

Le Maître, O. P.; Knio, O. M.; Moraes, A.

2015-06-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

Energy Technology Data Exchange (ETDEWEB)

Le Maître, O. P., E-mail: olm@limsi.fr [LIMSI-CNRS, UPR 3251, Orsay (France); Knio, O. M., E-mail: knio@duke.edu [Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708 (United States); Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa [King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance-based Salt Body Reconstruction

KAUST Repository

Ovcharenko, Oleg

2017-05-26

Seismic inversions of salt bodies are challenging when updating velocity models based on Born approximation- inspired gradient methods. We propose a variance-based method for velocity model reconstruction in regions complicated by massive salt bodies. The novel idea lies in retrieving useful information from simultaneous updates corresponding to different single frequencies. Instead of the commonly used averaging of single-iteration monofrequency gradients, our algorithm iteratively reconstructs salt bodies in an outer loop based on updates from a set of multiple frequencies after a few iterations of full-waveform inversion. The variance among these updates is used to identify areas where considerable cycle-skipping occurs. In such areas, we update velocities by interpolating maximum velocities within a certain region. The result of several recursive interpolations is later used as a new starting model to improve results of conventional full-waveform inversion. An application on part of the BP 2004 model highlights the evolution of the proposed approach and demonstrates its effectiveness.

Variance decomposition in stochastic simulators

KAUST Repository

Le Maî tre, O. P.; Knio, O. M.; Moraes, Alvaro

2015-01-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Time related total lactic acid bacteria population diversity and ...

African Journals Online (AJOL)

The total lactic acid bacterial community involved in the spontaneous fermentation of malted cowpea fortified cereal weaning food was investigated by phenotypically and cultivation independent method. A total of 74 out of the isolated 178 strains were Lactobacillus plantarum, 32 were Pediococcus acidilactici and over 60% ...

Minimum variance Monte Carlo importance sampling with parametric dependence

International Nuclear Information System (INIS)

Ragheb, M.M.H.; Halton, J.; Maynard, C.W.

1981-01-01

An approach for Monte Carlo Importance Sampling with parametric dependence is proposed. It depends upon obtaining by proper weighting over a single stage the overall functional dependence of the variance on the importance function parameter over a broad range of its values. Results corresponding to minimum variance are adapted and other results rejected. Numerical calculation for the estimation of intergrals are compared to Crude Monte Carlo. Results explain the occurrences of the effective biases (even though the theoretical bias is zero) and infinite variances which arise in calculations involving severe biasing and a moderate number of historis. Extension to particle transport applications is briefly discussed. The approach constitutes an extension of a theory on the application of Monte Carlo for the calculation of functional dependences introduced by Frolov and Chentsov to biasing, or importance sample calculations; and is a generalization which avoids nonconvergence to the optimal values in some cases of a multistage method for variance reduction introduced by Spanier. (orig.) [de

Host nutrition alters the variance in parasite transmission potential.

Science.gov (United States)

Vale, Pedro F; Choisy, Marc; Little, Tom J

2013-04-23

The environmental conditions experienced by hosts are known to affect their mean parasite transmission potential. How different conditions may affect the variance of transmission potential has received less attention, but is an important question for disease management, especially if specific ecological contexts are more likely to foster a few extremely infectious hosts. Using the obligate-killing bacterium Pasteuria ramosa and its crustacean host Daphnia magna, we analysed how host nutrition affected the variance of individual parasite loads, and, therefore, transmission potential. Under low food, individual parasite loads showed similar mean and variance, following a Poisson distribution. By contrast, among well-nourished hosts, parasite loads were right-skewed and overdispersed, following a negative binomial distribution. Abundant food may, therefore, yield individuals causing potentially more transmission than the population average. Measuring both the mean and variance of individual parasite loads in controlled experimental infections may offer a useful way of revealing risk factors for potential highly infectious hosts.

Exploring variance in residential electricity consumption: Household features and building properties

International Nuclear Information System (INIS)

Bartusch, Cajsa; Odlare, Monica; Wallin, Fredrik; Wester, Lars

2012-01-01

Highlights: ► Statistical analysis of variance are of considerable value in identifying key indicators for policy update. ► Variance in residential electricity use is partly explained by household features. ► Variance in residential electricity use is partly explained by building properties. ► Household behavior has a profound impact on individual electricity use. -- Abstract: Improved means of controlling electricity consumption plays an important part in boosting energy efficiency in the Swedish power market. Developing policy instruments to that end requires more in-depth statistics on electricity use in the residential sector, among other things. The aim of the study has accordingly been to assess the extent of variance in annual electricity consumption in single-family homes as well as to estimate the impact of household features and building properties in this respect using independent samples t-tests and one-way as well as univariate independent samples analyses of variance. Statistically significant variances associated with geographic area, heating system, number of family members, family composition, year of construction, electric water heater and electric underfloor heating have been established. The overall result of the analyses is nevertheless that variance in residential electricity consumption cannot be fully explained by independent variables related to household and building characteristics alone. As for the methodological approach, the results further suggest that methods for statistical analysis of variance are of considerable value in indentifying key indicators for policy update and development.

Discussion on variance reduction technique for shielding

Energy Technology Data Exchange (ETDEWEB)

Maekawa, Fujio [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

1998-03-01

As the task of the engineering design activity of the international thermonuclear fusion experimental reactor (ITER), on 316 type stainless steel (SS316) and the compound system of SS316 and water, the shielding experiment using the D-T neutron source of FNS in Japan Atomic Energy Research Institute has been carried out. However, in these analyses, enormous working time and computing time were required for determining the Weight Window parameter. Limitation or complication was felt when the variance reduction by Weight Window method of MCNP code was carried out. For the purpose of avoiding this difficulty, investigation was performed on the effectiveness of the variance reduction by cell importance method. The conditions of calculation in all cases are shown. As the results, the distribution of fractional standard deviation (FSD) related to neutrons and gamma-ray flux in the direction of shield depth is reported. There is the optimal importance change, and when importance was increased at the same rate as that of the attenuation of neutron or gamma-ray flux, the optimal variance reduction can be done. (K.I.)

Phenotypic integration and the evolution of signal repertoires: A case study of treefrog acoustic communication.

Science.gov (United States)

Reichert, Michael S; Höbel, Gerlinde

2018-03-01

Animal signals are inherently complex phenotypes with many interacting parts combining to elicit responses from receivers. The pattern of interrelationships between signal components reflects the extent to which each component is expressed, and responds to selection, either in concert with or independently of others. Furthermore, many species have complex repertoires consisting of multiple signal types used in different contexts, and common morphological and physiological constraints may result in interrelationships extending across the multiple signals in species' repertoires. The evolutionary significance of interrelationships between signal traits can be explored within the framework of phenotypic integration, which offers a suite of quantitative techniques to characterize complex phenotypes. In particular, these techniques allow for the assessment of modularity and integration, which describe, respectively, the extent to which sets of traits covary either independently or jointly. Although signal and repertoire complexity are thought to be major drivers of diversification and social evolution, few studies have explicitly measured the phenotypic integration of signals to investigate the evolution of diverse communication systems. We applied methods from phenotypic integration studies to quantify integration in the two primary vocalization types (advertisement and aggressive calls) in the treefrogs Hyla versicolor , Hyla cinerea, and Dendropsophus ebraccatus . We recorded male calls and calculated standardized phenotypic variance-covariance ( P ) matrices for characteristics within and across call types. We found significant integration across call types, but the strength of integration varied by species and corresponded with the acoustic similarity of the call types within each species. H. versicolor had the most modular advertisement and aggressive calls and the least acoustically similar call types. Additionally, P was robust to changing social competition

Capturing option anomalies with a variance-dependent pricing kernel

NARCIS (Netherlands)

Christoffersen, P.; Heston, S.; Jacobs, K.

2013-01-01

We develop a GARCH option model with a variance premium by combining the Heston-Nandi (2000) dynamic with a new pricing kernel that nests Rubinstein (1976) and Brennan (1979). While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is

29 CFR 1904.38 - Variances from the recordkeeping rule.

Science.gov (United States)

2010-07-01

..., DEPARTMENT OF LABOR RECORDING AND REPORTING OCCUPATIONAL INJURIES AND ILLNESSES Other OSHA Injury and Illness... he or she finds appropriate. (iv) If the Assistant Secretary grants your variance petition, OSHA will... Secretary is reviewing your variance petition. (4) If I have already been cited by OSHA for not following...

Can Optimism, Pessimism, Hope, Treatment Credibility and Treatment Expectancy Be Distinguished in Patients Undergoing Total Hip and Total Knee Arthroplasty?

Directory of Open Access Journals (Sweden)

Tsjitske M Haanstra

Full Text Available The constructs optimism, pessimism, hope, treatment credibility and treatment expectancy are associated with outcomes of medical treatment. While these constructs are grounded in different theoretical models, they nonetheless show some conceptual overlap. The purpose of this study was to examine whether currently available measurement instruments for these constructs capture the conceptual differences between these constructs within a treatment setting.Patients undergoing Total Hip and Total Knee Arthroplasty (THA and TKA (Total N = 361; 182 THA; 179 TKA, completed the Life Orientation Test-Revised for optimism and pessimism, the Hope Scale, the Credibility Expectancy Questionnaire for treatment credibility and treatment expectancy. Confirmatory factor analysis was used to examine whether the instruments measure distinct constructs. Four theory-driven models with one, two, four and five latent factors were evaluated using multiple fit indices and Δχ2 tests, followed by some posthoc models.The results of the theory driven confirmatory factor analysis showed that a five factor model in which all constructs loaded on separate factors yielded the most optimal and satisfactory fit. Posthoc, a bifactor model in which (besides the 5 separate factors a general factor is hypothesized accounting for the commonality of the items showed a significantly better fit than the five factor model. All specific factors, except for the hope factor, showed to explain a substantial amount of variance beyond the general factor.Based on our primary analyses we conclude that optimism, pessimism, hope, treatment credibility and treatment expectancy are distinguishable in THA and TKA patients. Postdoc, we determined that all constructs, except hope, showed substantial specific variance, while also sharing some general variance.

Can Optimism, Pessimism, Hope, Treatment Credibility and Treatment Expectancy Be Distinguished in Patients Undergoing Total Hip and Total Knee Arthroplasty?

Science.gov (United States)

Haanstra, Tsjitske M; Tilbury, Claire; Kamper, Steven J; Tordoir, Rutger L; Vliet Vlieland, Thea P M; Nelissen, Rob G H H; Cuijpers, Pim; de Vet, Henrica C W; Dekker, Joost; Knol, Dirk L; Ostelo, Raymond W

2015-01-01

The constructs optimism, pessimism, hope, treatment credibility and treatment expectancy are associated with outcomes of medical treatment. While these constructs are grounded in different theoretical models, they nonetheless show some conceptual overlap. The purpose of this study was to examine whether currently available measurement instruments for these constructs capture the conceptual differences between these constructs within a treatment setting. Patients undergoing Total Hip and Total Knee Arthroplasty (THA and TKA) (Total N = 361; 182 THA; 179 TKA), completed the Life Orientation Test-Revised for optimism and pessimism, the Hope Scale, the Credibility Expectancy Questionnaire for treatment credibility and treatment expectancy. Confirmatory factor analysis was used to examine whether the instruments measure distinct constructs. Four theory-driven models with one, two, four and five latent factors were evaluated using multiple fit indices and Δχ2 tests, followed by some posthoc models. The results of the theory driven confirmatory factor analysis showed that a five factor model in which all constructs loaded on separate factors yielded the most optimal and satisfactory fit. Posthoc, a bifactor model in which (besides the 5 separate factors) a general factor is hypothesized accounting for the commonality of the items showed a significantly better fit than the five factor model. All specific factors, except for the hope factor, showed to explain a substantial amount of variance beyond the general factor. Based on our primary analyses we conclude that optimism, pessimism, hope, treatment credibility and treatment expectancy are distinguishable in THA and TKA patients. Postdoc, we determined that all constructs, except hope, showed substantial specific variance, while also sharing some general variance.

Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes

KAUST Repository

AlShahrani, Mona; Hoehndorf, Robert

2018-01-01

In the past years, several methods have been developed to incorporate information about phenotypes into computational disease gene prioritization methods. These methods commonly compute the similarity between a disease's (or patient's) phenotypes and a database of gene-to-phenotype associations to find the phenotypically most similar match. A key limitation of these methods is their reliance on knowledge about phenotypes associated with particular genes which is highly incomplete in humans as well as in many model organisms such as the mouse. Results: We developed SmuDGE, a method that uses feature learning to generate vector-based representations of phenotypes associated with an entity. SmuDGE can be used as a trainable semantic similarity measure to compare two sets of phenotypes (such as between a disease and gene, or a disease and patient). More importantly, SmuDGE can generate phenotype representations for entities that are only indirectly associated with phenotypes through an interaction network; for this purpose, SmuDGE exploits background knowledge in interaction networks comprising of multiple types of interactions. We demonstrate that SmuDGE can match or outperform semantic similarity in phenotype-based disease gene prioritization, and furthermore significantly extends the coverage of phenotype-based methods to all genes in a connected interaction network.

Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes

KAUST Repository

Alshahrani, Mona

2018-04-30

In the past years, several methods have been developed to incorporate information about phenotypes into computational disease gene prioritization methods. These methods commonly compute the similarity between a disease\\'s (or patient\\'s) phenotypes and a database of gene-to-phenotype associations to find the phenotypically most similar match. A key limitation of these methods is their reliance on knowledge about phenotypes associated with particular genes which is highly incomplete in humans as well as in many model organisms such as the mouse. Results: We developed SmuDGE, a method that uses feature learning to generate vector-based representations of phenotypes associated with an entity. SmuDGE can be used as a trainable semantic similarity measure to compare two sets of phenotypes (such as between a disease and gene, or a disease and patient). More importantly, SmuDGE can generate phenotype representations for entities that are only indirectly associated with phenotypes through an interaction network; for this purpose, SmuDGE exploits background knowledge in interaction networks comprising of multiple types of interactions. We demonstrate that SmuDGE can match or outperform semantic similarity in phenotype-based disease gene prioritization, and furthermore significantly extends the coverage of phenotype-based methods to all genes in a connected interaction network.

Analysis of ulnar variance as a risk factor for developing scaphoid nonunion.

Science.gov (United States)

Lirola-Palmero, S; Salvà-Coll, G; Terrades-Cladera, F J

2015-01-01

Ulnar variance may be a risk factor of developing scaphoid non-union. A review was made of the posteroanterior wrist radiographs of 95 patients who were diagnosed of scaphoid fracture. All fractures with displacement less than 1mm treated conservatively were included. The ulnar variance was measured in all patients. Ulnar variance was measured in standard posteroanterior wrist radiographs of 95 patients. Eighteen patients (19%) developed scaphoid nonunion, with a mean value of ulnar variance of -1.34 (-/+ 0.85) mm (CI -2.25 - 0.41). Seventy seven patients (81%) healed correctly, and the mean value of ulnar variance was -0.04 (-/+ 1.85) mm (CI -0.46 - 0.38). A significant difference was observed in the distribution of ulnar variance (pvariance less than -1mm, and ulnar variance greater than -1mm. It appears that patients with ulnar variance less than -1mm had an OR 4.58 (CI 1.51 to 13.89) with pvariance less than -1mm have a greater risk of developing scaphoid nonunion, OR 4.58 (CI 1.51 to 13.89) with p<.007. Copyright © 2014 SECOT. Published by Elsevier Espana. All rights reserved.

Decomposition of variance in terms of conditional means

Directory of Open Access Journals (Sweden)

Alessandro Figà Talamanca

2013-05-01

Full Text Available Two different sets of data are used to test an apparently new approach to the analysis of the variance of a numerical variable which depends on qualitative variables. We suggest that this approach be used to complement other existing techniques to study the interdependence of the variables involved. According to our method, the variance is expressed as a sum of orthogonal components, obtained as differences of conditional means, with respect to the qualitative characters. The resulting expression for the variance depends on the ordering in which the characters are considered. We suggest an algorithm which leads to an ordering which is deemed natural. The first set of data concerns the score achieved by a population of students on an entrance examination based on a multiple choice test with 30 questions. In this case the qualitative characters are dyadic and correspond to correct or incorrect answer to each question. The second set of data concerns the delay to obtain the degree for a population of graduates of Italian universities. The variance in this case is analyzed with respect to a set of seven specific qualitative characters of the population studied (gender, previous education, working condition, parent's educational level, field of study, etc..

42 CFR 456.522 - Content of request for variance.

Science.gov (United States)

2010-10-01

... 42 Public Health 4 2010-10-01 2010-10-01 false Content of request for variance. 456.522 Section 456.522 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN... perform UR within the time requirements for which the variance is requested and its good faith efforts to...

On the Endogeneity of the Mean-Variance Efficient Frontier.

Science.gov (United States)

Somerville, R. A.; O'Connell, Paul G. J.

2002-01-01

Explains that the endogeneity of the efficient frontier in the mean-variance model of portfolio selection is commonly obscured in portfolio selection literature and in widely used textbooks. Demonstrates endogeneity and discusses the impact of parameter changes on the mean-variance efficient frontier and on the beta coefficients of individual…

Adaptive evolution of molecular phenotypes

International Nuclear Information System (INIS)

Held, Torsten; Nourmohammad, Armita; Lässig, Michael

2014-01-01

Molecular phenotypes link genomic information with organismic functions, fitness, and evolution. Quantitative traits are complex phenotypes that depend on multiple genomic loci. In this paper, we study the adaptive evolution of a quantitative trait under time-dependent selection, which arises from environmental changes or through fitness interactions with other co-evolving phenotypes. We analyze a model of trait evolution under mutations and genetic drift in a single-peak fitness seascape. The fitness peak performs a constrained random walk in the trait amplitude, which determines the time-dependent trait optimum in a given population. We derive analytical expressions for the distribution of the time-dependent trait divergence between populations and of the trait diversity within populations. Based on this solution, we develop a method to infer adaptive evolution of quantitative traits. Specifically, we show that the ratio of the average trait divergence and the diversity is a universal function of evolutionary time, which predicts the stabilizing strength and the driving rate of the fitness seascape. From an information-theoretic point of view, this function measures the macro-evolutionary entropy in a population ensemble, which determines the predictability of the evolutionary process. Our solution also quantifies two key characteristics of adapting populations: the cumulative fitness flux, which measures the total amount of adaptation, and the adaptive load, which is the fitness cost due to a population's lag behind the fitness peak. (paper)

Assessment of ulnar variance: a radiological investigation in a Dutch population

Energy Technology Data Exchange (ETDEWEB)

Schuurman, A.H. [Dept. of Plastic, Reconstructive and Hand Surgery, University Medical Centre, Utrecht (Netherlands); Dept. of Plastic Surgery, University Medical Centre, Utrecht (Netherlands); Maas, M.; Dijkstra, P.F. [Dept. of Radiology, Univ. of Amsterdam (Netherlands); Kauer, J.M.G. [Dept. of Anatomy and Embryology, Univ. of Nijmegen (Netherlands)

2001-11-01

Objective: A radiological study was performed to evaluate ulnar variance in 68 Dutch patients using an electronic digitizer compared with Palmer's concentric circle method. Using the digitizer method only, the effect of different wrist positions and grip on ulnar variance was then investigated. Finally the distribution of ulnar variance in the selected patients was investigated also using the digitizer method. Design and patients: All radiographs were performed with the wrist in a standard zero-rotation position (posteroanterior) and in supination (anteroposterior). Palmer's concentric circle method and an electronic digitizer connected to a personal computer were used to measure ulnar variance. The digitizer consists of a Plexiglas plate with an electronically activated grid beneath it. A radiograph is placed on the plate and a cursor activates a point on the grid. Three plots are marked on the radius and one plot on the most distal part of the ulnar head. The digitizer then determines the difference between a radius passing through the radius plots and the ulnar plot. Results and conclusions: Using the concentric circle method we found an ulna plus predominance, but an ulna minus predominance when using the digitizer method. Overall the ulnar variance distribution for Palmer's method was 41.9% ulna plus, 25.7% neutral and 32.4% ulna minus variance, and for the digitizer method was 40.4% ulna plus, 1.5% neutral and 58.1% ulna minus. The percentage ulnar variance greater than 1 mm on standard radiographs increased from 23% to 58% using the digitizer, with maximum grip, clearly demonstrating the (dynamic) effect of grip on ulnar variance. This almost threefold increase was found to be a significant difference. Significant differences were found between ulnar variance when different wrist positions were compared. (orig.)

Noise variance analysis using a flat panel x-ray detector: A method for additive noise assessment with application to breast CT applications

Energy Technology Data Exchange (ETDEWEB)

Yang Kai; Huang, Shih-Ying; Packard, Nathan J.; Boone, John M. [Department of Radiology, University of California, Davis Medical Center, 4860 Y Street, Suite 3100 Ellison Building, Sacramento, California 95817 (United States); Department of Radiology, University of California, Davis Medical Center, 4860 Y Street, Suite 3100 Ellison Building, Sacramento, California 95817 (United States) and Department of Biomedical Engineering, University of California, Davis, Davis, California, 95616 (United States)

2010-07-15

Purpose: A simplified linear model approach was proposed to accurately model the response of a flat panel detector used for breast CT (bCT). Methods: Individual detector pixel mean and variance were measured from bCT projection images acquired both in air and with a polyethylene cylinder, with the detector operating in both fixed low gain and dynamic gain mode. Once the coefficients of the linear model are determined, the fractional additive noise can be used as a quantitative metric to evaluate the system's efficiency in utilizing x-ray photons, including the performance of different gain modes of the detector. Results: Fractional additive noise increases as the object thickness increases or as the radiation dose to the detector decreases. For bCT scan techniques on the UC Davis prototype scanner (80 kVp, 500 views total, 30 frames/s), in the low gain mode, additive noise contributes 21% of the total pixel noise variance for a 10 cm object and 44% for a 17 cm object. With the dynamic gain mode, additive noise only represents approximately 2.6% of the total pixel noise variance for a 10 cm object and 7.3% for a 17 cm object. Conclusions: The existence of the signal-independent additive noise is the primary cause for a quadratic relationship between bCT noise variance and the inverse of radiation dose at the detector. With the knowledge of the additive noise contribution to experimentally acquired images, system modifications can be made to reduce the impact of additive noise and improve the quantum noise efficiency of the bCT system.

Variance and covariance calculations for nuclear materials accounting using ''MAVARIC''

International Nuclear Information System (INIS)

Nasseri, K.K.

1987-07-01

Determination of the detection sensitivity of a materials accounting system to the loss of special nuclear material (SNM) requires (1) obtaining a relation for the variance of the materials balance by propagation of the instrument errors for the measured quantities that appear in the materials balance equation and (2) substituting measured values and their error standard deviations into this relation and calculating the variance of the materials balance. MAVARIC (Materials Accounting VARIance Calculations) is a custom spreadsheet, designed using the second release of Lotus 1-2-3, that significantly reduces the effort required to make the necessary variance (and covariance) calculations needed to determine the detection sensitivity of a materials accounting system. Predefined macros within the spreadsheet allow the user to carry out long, tedious procedures with only a few keystrokes. MAVARIC requires that the user enter the following data into one of four data tables, depending on the type of the term in the materials balance equation; the SNM concentration, the bulk mass (or solution volume), the measurement error standard deviations, and the number of measurements made during an accounting period. The user can also specify if there are correlations between transfer terms. Based on these data entries, MAVARIC can calculate the variance of the materials balance and the square root of this variance, from which the detection sensitivity of the accounting system can be determined

A versatile omnibus test for detecting mean and variance heterogeneity.

Science.gov (United States)

Cao, Ying; Wei, Peng; Bailey, Matthew; Kauwe, John S K; Maxwell, Taylor J

2014-01-01

Recent research has revealed loci that display variance heterogeneity through various means such as biological disruption, linkage disequilibrium (LD), gene-by-gene (G × G), or gene-by-environment interaction. We propose a versatile likelihood ratio test that allows joint testing for mean and variance heterogeneity (LRT(MV)) or either effect alone (LRT(M) or LRT(V)) in the presence of covariates. Using extensive simulations for our method and others, we found that all parametric tests were sensitive to nonnormality regardless of any trait transformations. Coupling our test with the parametric bootstrap solves this issue. Using simulations and empirical data from a known mean-only functional variant, we demonstrate how LD can produce variance-heterogeneity loci (vQTL) in a predictable fashion based on differential allele frequencies, high D', and relatively low r² values. We propose that a joint test for mean and variance heterogeneity is more powerful than a variance-only test for detecting vQTL. This takes advantage of loci that also have mean effects without sacrificing much power to detect variance only effects. We discuss using vQTL as an approach to detect G × G interactions and also how vQTL are related to relationship loci, and how both can create prior hypothesis for each other and reveal the relationships between traits and possibly between components of a composite trait.

Variance and covariance calculations for nuclear materials accounting using 'MAVARIC'

International Nuclear Information System (INIS)

Nasseri, K.K.

1987-01-01

Determination of the detection sensitivity of a materials accounting system to the loss of special nuclear material (SNM) requires (1) obtaining a relation for the variance of the materials balance by propagation of the instrument errors for the measured quantities that appear in the materials balance equation and (2) substituting measured values and their error standard deviations into this relation and calculating the variance of the materials balance. MAVARIC (Materials Accounting VARIance Calculations) is a custom spreadsheet, designed using the second release of Lotus 1-2-3, that significantly reduces the effort required to make the necessary variance (and covariance) calculations needed to determine the detection sensitivity of a materials accounting system. Predefined macros within the spreadsheet allow the user to carry out long, tedious procedures with only a few keystrokes. MAVARIC requires that the user enter the following data into one of four data tables, depending on the type of the term in the materials balance equation; the SNM concentration, the bulk mass (or solution volume), the measurement error standard deviations, and the number of measurements made during an accounting period. The user can also specify if there are correlations between transfer terms. Based on these data entries, MAVARIC can calculate the variance of the materials balance and the square root of this variance, from which the detection sensitivity of the accounting system can be determined

Operationalizing Proneness to Externalizing Psychopathology as a Multivariate Psychophysiological Phenotype

Science.gov (United States)

Nelson, Lindsay D.; Patrick, Christopher J.; Bernat, Edward M.

2010-01-01

The externalizing dimension is viewed as a broad dispositional factor underlying risk for numerous disinhibitory disorders. Prior work has documented deficits in event-related brain potential (ERP) responses in individuals prone to externalizing problems. Here, we constructed a direct physiological index of externalizing vulnerability from three ERP indicators and evaluated its validity in relation to criterion measures in two distinct domains: psychometric and physiological. The index was derived from three ERP measures that covaried in their relations with externalizing proneness the error-related negativity and two variants of the P3. Scores on this ERP composite predicted psychometric criterion variables and accounted for externalizing-related variance in P3 response from a separate task. These findings illustrate how a diagnostic construct can be operationalized as a composite (multivariate) psychophysiological variable (phenotype). PMID:20573054

Global Variance Risk Premium and Forex Return Predictability

OpenAIRE

Aloosh, Arash

2014-01-01

In a long-run risk model with stochastic volatility and frictionless markets, I express expected forex returns as a function of consumption growth variances and stock variance risk premiums (VRPs)—the difference between the risk-neutral and statistical expectations of market return variation. This provides a motivation for using the forward-looking information available in stock market volatility indices to predict forex returns. Empirically, I find that stock VRPs predict forex returns at a ...

Improving persistence in red clover: Insights from QTL analysis and comparative phenotypic evaluation

DEFF Research Database (Denmark)

Herrmann, Dorris; Boller, Beat; Studer, Bruno

2008-01-01

, persistence is difficult to improve. The objectives of this study were to optimize the phenotypic evaluation of persistence, to identify quantitative trait loci (QTLs) for this important trait, and to investigate the association of persistence with other important traits. A weighted average of vigor scores...... assessed during two winters and three growing seasons was identified as the optimal method to phenotype persistence. For this index, one QTL explaining 12.2% of the total phenotypic variation was identified. While there was no negative correlation between persistence and seed yield, persistence...

Phenotypic plasticity, costs of phenotypes, and costs of plasticity

DEFF Research Database (Denmark)

Callahan, Hilary S; Maughan, Heather; Steiner, Uli

2008-01-01

Why are some traits constitutive and others inducible? The term costs often appears in work addressing this issue but may be ambiguously defined. This review distinguishes two conceptually distinct types of costs: phenotypic costs and plasticity costs. Phenotypic costs are assessed from patterns...... of covariation, typically between a focal trait and a separate trait relevant to fitness. Plasticity costs, separable from phenotypic costs, are gauged by comparing the fitness of genotypes with equivalent phenotypes within two environments but differing in plasticity and fitness. Subtleties associated with both...... types of costs are illustrated by a body of work addressing predator-induced plasticity. Such subtleties, and potential interplay between the two types of costs, have also been addressed, often in studies involving genetic model organisms. In some instances, investigators have pinpointed the mechanistic...

29 CFR 1920.2 - Variances.

Science.gov (United States)

2010-07-01

...) PROCEDURE FOR VARIATIONS FROM SAFETY AND HEALTH REGULATIONS UNDER THE LONGSHOREMEN'S AND HARBOR WORKERS...) or 6(d) of the Williams-Steiger Occupational Safety and Health Act of 1970 (29 U.S.C. 655). The... under the Williams-Steiger Occupational Safety and Health Act of 1970, and any variance from §§ 1910.13...

Zero-intelligence realized variance estimation

NARCIS (Netherlands)

Gatheral, J.; Oomen, R.C.A.

2010-01-01

Given a time series of intra-day tick-by-tick price data, how can realized variance be estimated? The obvious estimator—the sum of squared returns between trades—is biased by microstructure effects such as bid-ask bounce and so in the past, practitioners were advised to drop most of the data and

A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

Science.gov (United States)

Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

2017-11-01

Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this

The mean and variance of phylogenetic diversity under rarefaction.

Science.gov (United States)

Nipperess, David A; Matsen, Frederick A

2013-06-01

Phylogenetic diversity (PD) depends on sampling depth, which complicates the comparison of PD between samples of different depth. One approach to dealing with differing sample depth for a given diversity statistic is to rarefy, which means to take a random subset of a given size of the original sample. Exact analytical formulae for the mean and variance of species richness under rarefaction have existed for some time but no such solution exists for PD.We have derived exact formulae for the mean and variance of PD under rarefaction. We confirm that these formulae are correct by comparing exact solution mean and variance to that calculated by repeated random (Monte Carlo) subsampling of a dataset of stem counts of woody shrubs of Toohey Forest, Queensland, Australia. We also demonstrate the application of the method using two examples: identifying hotspots of mammalian diversity in Australasian ecoregions, and characterising the human vaginal microbiome.There is a very high degree of correspondence between the analytical and random subsampling methods for calculating mean and variance of PD under rarefaction, although the Monte Carlo method requires a large number of random draws to converge on the exact solution for the variance.Rarefaction of mammalian PD of ecoregions in Australasia to a common standard of 25 species reveals very different rank orderings of ecoregions, indicating quite different hotspots of diversity than those obtained for unrarefied PD. The application of these methods to the vaginal microbiome shows that a classical score used to quantify bacterial vaginosis is correlated with the shape of the rarefaction curve.The analytical formulae for the mean and variance of PD under rarefaction are both exact and more efficient than repeated subsampling. Rarefaction of PD allows for many applications where comparisons of samples of different depth is required.

Using variances to comply with resource conservation and recovery act treatment standards

International Nuclear Information System (INIS)

Ranek, N.L.

2002-01-01

When a waste generated, treated, or disposed of at a site in the United States is classified as hazardous under the Resource Conservation and Recovery Act and is destined for land disposal, the waste manager responsible for that site must select an approach to comply with land disposal restrictions (LDR) treatment standards. This paper focuses on the approach of obtaining a variance from existing, applicable LDR treatment standards. It describes the types of available variances, which include (1) determination of equivalent treatment (DET); (2) treatability variance; and (3) treatment variance for contaminated soil. The process for obtaining each type of variance is also described. Data are presented showing that historically the U.S. Environmental Protection Agency (EPA) processed DET petitions within one year of their date of submission. However, a 1999 EPA policy change added public participation to the DET petition review, which may lengthen processing time in the future. Regarding site-specific treatability variances, data are presented showing an EPA processing time of between 10 and 16 months. Only one generically applicable treatability variance has been granted, which took 30 months to process. No treatment variances for contaminated soil, which were added to the federal LDR program in 1998, are identified as having been granted.

Determinations of dose mean of specific energy for conventional x-rays by variance-measurements

International Nuclear Information System (INIS)

Forsberg, B.; Jensen, M.; Lindborg, L.; Samuelson, G.

1978-05-01

The dose mean value (zeta) of specific energy of a single event distribution is related to the variance of a multiple event distribution in a simple way. It is thus possible to determine zeta from measurements in high dose rates through observations of the variations in the ionization current from for instance an ionization chamber, if other parameters contribute negligibly to the total variance. With this method is has earlier been possible to obtain results down to about 10 nm in a beam of Co60-γ rays, which is one order of magnitude smaller than the sizes obtainable with the traditional technique. This advantage together with the suggestion that zeta could be an important parameter in radiobiology make further studies of the applications of the technique motivated. So far only data from measurements in beams of a radioactive nuclide has been reported. This paper contains results from measurements in a highly stabilized X-ray beam. The preliminary analysis shows that the variance technique has given reasonable results for object sizes in the region of 0.08 μm to 20 μm (100 kV, 1.6 Al, HVL 0.14 mm Cu). The results were obtained with a proportional counter except for the larger object sizes, where an ionization chamber was used. The measurements were performed at dose rates between 1 Gy/h and 40 Gy/h. (author)

Genetic Variation in Schizophrenia Liability is Shared With Intellectual Ability and Brain Structure.

Science.gov (United States)

Bohlken, Marc M; Brouwer, Rachel M; Mandl, René C W; Kahn, René S; Hulshoff Pol, Hilleke E

2016-09-01

Alterations in intellectual ability and brain structure are important genetic markers for schizophrenia liability. How variations in these phenotypes interact with variance in schizophrenia liability due to genetic or environmental factors is an area of active investigation. Studying these genetic markers using a multivariate twin modeling approach can provide novel leads for (genetic) pathways of schizophrenia development. In a sample of 70 twins discordant for schizophrenia and 130 healthy control twins, structural equation modeling was applied to quantify unique contributions of genetic and environmental factors on human brain structure (cortical thickness, cortical surface and global white matter fractional anisotropy [FA]), intellectual ability and schizophrenia liability. In total, up to 28.1% of the genetic variance (22.8% of total variance) in schizophrenia liability was shared with intelligence quotient (IQ), global-FA, cortical thickness, and cortical surface. The strongest contributor was IQ, sharing on average 16.4% of the genetic variance in schizophrenia liability, followed by cortical thickness (6.3%), global-FA (4.7%) and cortical surface (0.5%). Furthermore, we found that up to 57.4% of the variation due to environmental factors (4.6% of total variance) in schizophrenia was shared with IQ (34.2%) and cortical surface (13.4%). Intellectual ability, FA and cortical thickness show significant and independent shared genetic variance with schizophrenia liability. This suggests that measuring brain-imaging phenotypes helps explain genetic variance in schizophrenia liability that is not captured by variation in IQ. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Total synthesis and biological investigation of (-)-promysalin.

Science.gov (United States)

Steele, Andrew D; Knouse, Kyle W; Keohane, Colleen E; Wuest, William M

2015-06-17

Compounds that specifically target pathogenic bacteria are greatly needed, and identifying the method by which they act would provide new avenues of treatment. Herein we report the concise, high-yielding total synthesis (eight steps, 35% yield) of promysalin, a natural product that displays antivirulence phenotypes against pathogenic bacteria. Guided by bioinformatics, four diastereomers were synthesized, and the relative and absolute stereochemistries were confirmed by spectral and biological analysis. Finally, we show for the first time that promysalin displays two antivirulence phenotypes: the dispersion of mature biofilms and the inhibition of pyoverdine production, hinting at a unique pathogenic-specific mechanism of action.

Gini estimation under infinite variance

NARCIS (Netherlands)

A. Fontanari (Andrea); N.N. Taleb (Nassim Nicholas); P. Cirillo (Pasquale)

2018-01-01

textabstractWe study the problems related to the estimation of the Gini index in presence of a fat-tailed data generating process, i.e. one in the stable distribution class with finite mean but infinite variance (i.e. with tail index α∈(1,2)). We show that, in such a case, the Gini coefficient

Variance analysis of forecasted streamflow maxima in a wet temperate climate

Science.gov (United States)

Al Aamery, Nabil; Fox, James F.; Snyder, Mark; Chandramouli, Chandra V.

2018-05-01

Coupling global climate models, hydrologic models and extreme value analysis provides a method to forecast streamflow maxima, however the elusive variance structure of the results hinders confidence in application. Directly correcting the bias of forecasts using the relative change between forecast and control simulations has been shown to marginalize hydrologic uncertainty, reduce model bias, and remove systematic variance when predicting mean monthly and mean annual streamflow, prompting our investigation for maxima streamflow. We assess the variance structure of streamflow maxima using realizations of emission scenario, global climate model type and project phase, downscaling methods, bias correction, extreme value methods, and hydrologic model inputs and parameterization. Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima versus peak over threshold method applied, albeit we stress that researchers strictly adhere to rules from extreme value theory when applying the peak over threshold method. Regardless of which method is applied, extreme value model fitting does add variance to the projection, and the variance is an increasing function of the return period. Unlike the relative change of mean streamflow, results show that the variance of the maxima's relative change was dependent on all climate model factors tested as well as hydrologic model inputs and calibration. Ensemble projections forecast an increase of streamflow maxima for 2050 with pronounced forecast standard error, including an increase of +30(±21), +38(±34) and +51(±85)% for 2, 20 and 100 year streamflow events for the wet temperate region studied. The variance of maxima projections was dominated by climate model factors and extreme value analyses.

Genet and tic vari d seed iability yield t oc y and h traits i cciden ...

African Journals Online (AJOL)

SAM

between two variables; δ2x is the genotypic or phenotypic variance of the variable x, δ2y is the genotypic or phenotypic variance of the variable yield y. .... var = genotypic variance; Env var = environmental variance; PCV = phenotypic coefficient of variability; GCV = genotypic coefficient of variability; Gen adv% = genetic ...

Partitioning of genomic variance using biological pathways

DEFF Research Database (Denmark)

Edwards, Stefan McKinnon; Janss, Luc; Madsen, Per

and that these variants are enriched for genes that are connected in biological pathways or for likely functional effects on genes. These biological findings provide valuable insight for developing better genomic models. These are statistical models for predicting complex trait phenotypes on the basis of SNP......-data and trait phenotypes and can account for a much larger fraction of the heritable component. A disadvantage is that this “black-box” modelling approach conceals the biological mechanisms underlying the trait. We propose to open the “black-box” by building SNP-set genomic models that evaluate the collective...... action of multiple SNPs in genes, biological pathways or other external findings on the trait phenotype. As proof of concept we have tested the modelling framework on several traits in dairy cattle....

Continuous-Time Mean-Variance Portfolio Selection: A Stochastic LQ Framework

International Nuclear Information System (INIS)

Zhou, X.Y.; Li, D.

2000-01-01

This paper is concerned with a continuous-time mean-variance portfolio selection model that is formulated as a bicriteria optimization problem. The objective is to maximize the expected terminal return and minimize the variance of the terminal wealth. By putting weights on the two criteria one obtains a single objective stochastic control problem which is however not in the standard form due to the variance term involved. It is shown that this nonstandard problem can be 'embedded' into a class of auxiliary stochastic linear-quadratic (LQ) problems. The stochastic LQ control model proves to be an appropriate and effective framework to study the mean-variance problem in light of the recent development on general stochastic LQ problems with indefinite control weighting matrices. This gives rise to the efficient frontier in a closed form for the original portfolio selection problem

Replica approach to mean-variance portfolio optimization

Science.gov (United States)

Varga-Haszonits, Istvan; Caccioli, Fabio; Kondor, Imre

2016-12-01

We consider the problem of mean-variance portfolio optimization for a generic covariance matrix subject to the budget constraint and the constraint for the expected return, with the application of the replica method borrowed from the statistical physics of disordered systems. We find that the replica symmetry of the solution does not need to be assumed, but emerges as the unique solution of the optimization problem. We also check the stability of this solution and find that the eigenvalues of the Hessian are positive for r  =  N/T  optimal in-sample variance is found to vanish at the critical point inversely proportional to the divergent estimation error.

Analysis on endocrine and metabolic features of different phenotypes of polycystic ovary syndrome patients.

Science.gov (United States)

Li, Feng; Yao, Li; Wu, Hong; Cao, Shihong

2016-09-01

To discuss the manifestations of endocrine and metabolism for polycystic ovary syndrome patients with different phenotype. This study selected 226 cases of Rotterdam Standard diagnosed polycystic ovary syndrome patients in People's Hospital of Zhengzhou from October 2013 to February 2015. The control group was the 100 cases of non hyperandrogen menstrual women as the control group. Polycystic ovary syndrome included 4 phenotype: /or anovulatio (O) combined with hyperandrogenism (H) and polycystic ovary morphology (P), phenotype of O and P, phenotype of H and P, and phenotype of O and P. All patients were detected for the clinical endocrine and metabolism related parameters. The phenotype of O and P occupied 55.8%, it had significant difference on the comparison between control group and the luteinizing hormone (LH) and luteinizing hormone/follicle stimulating hormone (LH/FSH) of phenotype of O, H and P, phenotype of O and H and phenotype of O and P; the testosterone (T) of phenotype of O,H and P and phenotype of O and H was apparently higher than phenotype of O and P and control group; The total cholesterol (TC) and triglyceride (TG) in phenotype of O, H and P was greatly higher than phenotype of O and P and control group. The phenotype of O and P was the most common phenotype in PCOS patients. It was same for the clinical endocrine and metabolism of two classic characteristics in PCOS. Compared to other PCOS phenotype, the metabolism in phenotype of O and P was lower. The phenotype classification of PCOS patients could better guide clinical individualized treatment in patients with PCOS.

Cassava brown streak disease in Rwanda, the associated viruses and disease phenotypes.

Science.gov (United States)

Munganyinka, E; Ateka, E M; Kihurani, A W; Kanyange, M C; Tairo, F; Sseruwagi, P; Ndunguru, J

2018-02-01

Cassava brown streak disease (CBSD) was first observed on cassava ( Manihot esculenta ) in Rwanda in 2009. In 2014 eight major cassava-growing districts in the country were surveyed to determine the distribution and variability of symptom phenotypes associated with CBSD, and the genetic diversity of cassava brown streak viruses. Distribution of the CBSD symptom phenotypes and their combinations varied greatly between districts, cultivars and their associated viruses. The symptoms on leaf alone recorded the highest (32.2%) incidence, followed by roots (25.7%), leaf + stem (20.3%), leaf + root (10.4%), leaf + stem + root (5.2%), stem + root (3.7%), and stem (2.5%) symptoms. Analysis by RT-PCR showed that single infections of Ugandan cassava brown streak virus (UCBSV) were most common (74.2% of total infections) and associated with all the seven phenotypes studied. Single infections of Cassava brown streak virus (CBSV) were predominant (15.3% of total infections) in CBSD-affected plants showing symptoms on stems alone. Mixed infections (CBSV + UCBSV) comprised 10.5% of total infections and predominated in the combinations of leaf + stem + root phenotypes. Phylogenetic analysis and the estimates of evolutionary divergence, using partial sequences (210 nt) of the coat protein gene, revealed that in Rwanda there is one type of CBSV and an indication of diverse UCBSV. This study is the first to report the occurrence and distribution of both CBSV and UCBSV based on molecular techniques in Rwanda.

Random phenotypic variation of yeast (Saccharomyces cerevisiae) single-gene knockouts fits a double pareto-lognormal distribution.

Science.gov (United States)

Graham, John H; Robb, Daniel T; Poe, Amy R

2012-01-01

Distributed robustness is thought to influence the buffering of random phenotypic variation through the scale-free topology of gene regulatory, metabolic, and protein-protein interaction networks. If this hypothesis is true, then the phenotypic response to the perturbation of particular nodes in such a network should be proportional to the number of links those nodes make with neighboring nodes. This suggests a probability distribution approximating an inverse power-law of random phenotypic variation. Zero phenotypic variation, however, is impossible, because random molecular and cellular processes are essential to normal development. Consequently, a more realistic distribution should have a y-intercept close to zero in the lower tail, a mode greater than zero, and a long (fat) upper tail. The double Pareto-lognormal (DPLN) distribution is an ideal candidate distribution. It consists of a mixture of a lognormal body and upper and lower power-law tails. If our assumptions are true, the DPLN distribution should provide a better fit to random phenotypic variation in a large series of single-gene knockout lines than other skewed or symmetrical distributions. We fit a large published data set of single-gene knockout lines in Saccharomyces cerevisiae to seven different probability distributions: DPLN, right Pareto-lognormal (RPLN), left Pareto-lognormal (LPLN), normal, lognormal, exponential, and Pareto. The best model was judged by the Akaike Information Criterion (AIC). Phenotypic variation among gene knockouts in S. cerevisiae fits a double Pareto-lognormal (DPLN) distribution better than any of the alternative distributions, including the right Pareto-lognormal and lognormal distributions. A DPLN distribution is consistent with the hypothesis that developmental stability is mediated, in part, by distributed robustness, the resilience of gene regulatory, metabolic, and protein-protein interaction networks. Alternatively, multiplicative cell growth, and the mixing of

Realized Variance and Market Microstructure Noise

DEFF Research Database (Denmark)

Hansen, Peter R.; Lunde, Asger

2006-01-01

We study market microstructure noise in high-frequency data and analyze its implications for the realized variance (RV) under a general specification for the noise. We show that kernel-based estimators can unearth important characteristics of market microstructure noise and that a simple kernel......-based estimator dominates the RV for the estimation of integrated variance (IV). An empirical analysis of the Dow Jones Industrial Average stocks reveals that market microstructure noise its time-dependent and correlated with increments in the efficient price. This has important implications for volatility...... estimation based on high-frequency data. Finally, we apply cointegration techniques to decompose transaction prices and bid-ask quotes into an estimate of the efficient price and noise. This framework enables us to study the dynamic effects on transaction prices and quotes caused by changes in the efficient...

Spot Variance Path Estimation and its Application to High Frequency Jump Testing

NARCIS (Netherlands)

Bos, C.S.; Janus, P.; Koopman, S.J.

2012-01-01

This paper considers spot variance path estimation from datasets of intraday high-frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects, and microstructure noise. We rely on parametric and nonparametric methods. The estimated spot variance path can be used to

International survey of primary and revision total knee replacement

NARCIS (Netherlands)

Kurtz, Steven M.; Ong, Kevin L.; Lau, Edmund; Widmer, Marcel; Maravic, Milka; Gomez-Barrena, Enrique; de Pina, Maria de Fatima; Manno, Valerio; Torre, Marina; Walter, William L.; de Steiger, Richard; Geesink, Rudolph G. T.; Peltola, Mikko; Roeder, Christoph

2011-01-01

Total knee arthroplasty (TKA) is currently the international standard of care for treating degenerative and rheumatologic knee joint disease, as well as certain knee joint fractures. We sought to answer the following three research questions: (1) What is the international variance in primary and

ANALISIS PORTOFOLIO RESAMPLED EFFICIENT FRONTIER BERDASARKAN OPTIMASI MEAN-VARIANCE

OpenAIRE

Abdurakhman, Abdurakhman

2008-01-01

Keputusan alokasi asset yang tepat pada investasi portofolio dapat memaksimalkan keuntungan dan atau meminimalkan risiko. Metode yang sering dipakai dalam optimasi portofolio adalah metode Mean-Variance Markowitz. Dalam prakteknya, metode ini mempunyai kelemahan tidak terlalu stabil. Sedikit perubahan dalam estimasi parameter input menyebabkan perubahan besar pada komposisi portofolio. Untuk itu dikembangkan metode optimasi portofolio yang dapat mengatasi ketidakstabilan metode Mean-Variance ...

Mean-variance Optimal Reinsurance-investment Strategy in Continuous Time

OpenAIRE

Daheng Peng; Fang Zhang

2017-01-01

In this paper, Lagrange method is used to solve the continuous-time mean-variance reinsurance-investment problem. Proportional reinsurance, multiple risky assets and risk-free asset are considered synthetically in the optimal strategy for insurers. By solving the backward stochastic differential equation for the Lagrange multiplier, we get the mean-variance optimal reinsurance-investment strategy and its effective frontier in explicit forms.

The asymptotic variance of departures in critically loaded queues

NARCIS (Netherlands)

Al Hanbali, Ahmad; Mandjes, M.R.H.; Nazarathy, Y.; Whitt, W.

2011-01-01

We consider the asymptotic variance of the departure counting process D(t) of the GI/G/1 queue; D(t) denotes the number of departures up to time t. We focus on the case where the system load ϱ equals 1, and prove that the asymptotic variance rate satisfies limt→∞varD(t) / t = λ(1 - 2 / π)(ca2 +

Coupled bias-variance tradeoff for cross-pose face recognition.

Science.gov (United States)

Li, Annan; Shan, Shiguang; Gao, Wen

2012-01-01

Subspace-based face representation can be looked as a regression problem. From this viewpoint, we first revisited the problem of recognizing faces across pose differences, which is a bottleneck in face recognition. Then, we propose a new approach for cross-pose face recognition using a regressor with a coupled bias-variance tradeoff. We found that striking a coupled balance between bias and variance in regression for different poses could improve the regressor-based cross-pose face representation, i.e., the regressor can be more stable against a pose difference. With the basic idea, ridge regression and lasso regression are explored. Experimental results on CMU PIE, the FERET, and the Multi-PIE face databases show that the proposed bias-variance tradeoff can achieve considerable reinforcement in recognition performance.

Monte Carlo variance reduction approaches for non-Boltzmann tallies

International Nuclear Information System (INIS)

Booth, T.E.

1992-12-01

Quantities that depend on the collective effects of groups of particles cannot be obtained from the standard Boltzmann transport equation. Monte Carlo estimates of these quantities are called non-Boltzmann tallies and have become increasingly important recently. Standard Monte Carlo variance reduction techniques were designed for tallies based on individual particles rather than groups of particles. Experience with non-Boltzmann tallies and analog Monte Carlo has demonstrated the severe limitations of analog Monte Carlo for many non-Boltzmann tallies. In fact, many calculations absolutely require variance reduction methods to achieve practical computation times. Three different approaches to variance reduction for non-Boltzmann tallies are described and shown to be unbiased. The advantages and disadvantages of each of the approaches are discussed

Explicit formulas for the variance of discounted life-cycle cost

International Nuclear Information System (INIS)

Noortwijk, Jan M. van

2003-01-01

In life-cycle costing analyses, optimal design is usually achieved by minimising the expected value of the discounted costs. As well as the expected value, the corresponding variance may be useful for estimating, for example, the uncertainty bounds of the calculated discounted costs. However, general explicit formulas for calculating the variance of the discounted costs over an unbounded time horizon are not yet available. In this paper, explicit formulas for this variance are presented. They can be easily implemented in software to optimise structural design and maintenance management. The use of the mathematical results is illustrated with some examples

Quantitative genetic analysis of total glucosinolate, oil and protein ...

African Journals Online (AJOL)

Quantitative genetic analysis of total glucosinolate, oil and protein contents in Ethiopian mustard ( Brassica carinata A. Braun) ... Seeds were analyzed using HPLC (glucosinolates), NMR (oil) and NIRS (protein). Analyses of variance, Hayman's method of diallel analysis and a mixed linear model of genetic analysis were ...

Mean-variance Optimal Reinsurance-investment Strategy in Continuous Time

Directory of Open Access Journals (Sweden)

Daheng Peng

2017-10-01

Full Text Available In this paper, Lagrange method is used to solve the continuous-time mean-variance reinsurance-investment problem. Proportional reinsurance, multiple risky assets and risk-free asset are considered synthetically in the optimal strategy for insurers. By solving the backward stochastic differential equation for the Lagrange multiplier, we get the mean-variance optimal reinsurance-investment strategy and its effective frontier in explicit forms.

Increased gender variance in autism spectrum disorders and attention deficit hyperactivity disorder.

Science.gov (United States)

Strang, John F; Kenworthy, Lauren; Dominska, Aleksandra; Sokoloff, Jennifer; Kenealy, Laura E; Berl, Madison; Walsh, Karin; Menvielle, Edgardo; Slesaransky-Poe, Graciela; Kim, Kyung-Eun; Luong-Tran, Caroline; Meagher, Haley; Wallace, Gregory L

2014-11-01

Evidence suggests over-representation of autism spectrum disorders (ASDs) and behavioral difficulties among people referred for gender issues, but rates of the wish to be the other gender (gender variance) among different neurodevelopmental disorders are unknown. This chart review study explored rates of gender variance as reported by parents on the Child Behavior Checklist (CBCL) in children with different neurodevelopmental disorders: ASD (N = 147, 24 females and 123 males), attention deficit hyperactivity disorder (ADHD; N = 126, 38 females and 88 males), or a medical neurodevelopmental disorder (N = 116, 57 females and 59 males), were compared with two non-referred groups [control sample (N = 165, 61 females and 104 males) and non-referred participants in the CBCL standardization sample (N = 1,605, 754 females and 851 males)]. Significantly greater proportions of participants with ASD (5.4%) or ADHD (4.8%) had parent reported gender variance than in the combined medical group (1.7%) or non-referred comparison groups (0-0.7%). As compared to non-referred comparisons, participants with ASD were 7.59 times more likely to express gender variance; participants with ADHD were 6.64 times more likely to express gender variance. The medical neurodevelopmental disorder group did not differ from non-referred samples in likelihood to express gender variance. Gender variance was related to elevated emotional symptoms in ADHD, but not in ASD. After accounting for sex ratio differences between the neurodevelopmental disorder and non-referred comparison groups, gender variance occurred equally in females and males.

The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease

Science.gov (United States)

Groza, Tudor; Köhler, Sebastian; Moldenhauer, Dawid; Vasilevsky, Nicole; Baynam, Gareth; Zemojtel, Tomasz; Schriml, Lynn Marie; Kibbe, Warren Alden; Schofield, Paul N.; Beck, Tim; Vasant, Drashtti; Brookes, Anthony J.; Zankl, Andreas; Washington, Nicole L.; Mungall, Christopher J.; Lewis, Suzanna E.; Haendel, Melissa A.; Parkinson, Helen; Robinson, Peter N.

2015-01-01

The Human Phenotype Ontology (HPO) is widely used in the rare disease community for differential diagnostics, phenotype-driven analysis of next-generation sequence-variation data, and translational research, but a comparable resource has not been available for common disease. Here, we have developed a concept-recognition procedure that analyzes the frequencies of HPO disease annotations as identified in over five million PubMed abstracts by employing an iterative procedure to optimize precision and recall of the identified terms. We derived disease models for 3,145 common human diseases comprising a total of 132,006 HPO annotations. The HPO now comprises over 250,000 phenotypic annotations for over 10,000 rare and common diseases and can be used for examining the phenotypic overlap among common diseases that share risk alleles, as well as between Mendelian diseases and common diseases linked by genomic location. The annotations, as well as the HPO itself, are freely available. PMID:26119816

A mean–variance objective for robust production optimization in uncertain geological scenarios

DEFF Research Database (Denmark)

Capolei, Andrea; Suwartadi, Eka; Foss, Bjarne

2014-01-01

directly. In the mean–variance bi-criterion objective function risk appears directly, it also considers an ensemble of reservoir models, and has robust optimization as a special extreme case. The mean–variance objective is common for portfolio optimization problems in finance. The Markowitz portfolio...... optimization problem is the original and simplest example of a mean–variance criterion for mitigating risk. Risk is mitigated in oil production by including both the expected NPV (mean of NPV) and the risk (variance of NPV) for the ensemble of possible reservoir models. With the inclusion of the risk...

Asymptotic variance of grey-scale surface area estimators

DEFF Research Database (Denmark)

Svane, Anne Marie

Grey-scale local algorithms have been suggested as a fast way of estimating surface area from grey-scale digital images. Their asymptotic mean has already been described. In this paper, the asymptotic behaviour of the variance is studied in isotropic and sufficiently smooth settings, resulting...... in a general asymptotic bound. For compact convex sets with nowhere vanishing Gaussian curvature, the asymptotics can be described more explicitly. As in the case of volume estimators, the variance is decomposed into a lattice sum and an oscillating term of at most the same magnitude....

Prediction-error variance in Bayesian model updating: a comparative study

Science.gov (United States)

Asadollahi, Parisa; Li, Jian; Huang, Yong

2017-04-01

In Bayesian model updating, the likelihood function is commonly formulated by stochastic embedding in which the maximum information entropy probability model of prediction error variances plays an important role and it is Gaussian distribution subject to the first two moments as constraints. The selection of prediction error variances can be formulated as a model class selection problem, which automatically involves a trade-off between the average data-fit of the model class and the information it extracts from the data. Therefore, it is critical for the robustness in the updating of the structural model especially in the presence of modeling errors. To date, three ways of considering prediction error variances have been seem in the literature: 1) setting constant values empirically, 2) estimating them based on the goodness-of-fit of the measured data, and 3) updating them as uncertain parameters by applying Bayes' Theorem at the model class level. In this paper, the effect of different strategies to deal with the prediction error variances on the model updating performance is investigated explicitly. A six-story shear building model with six uncertain stiffness parameters is employed as an illustrative example. Transitional Markov Chain Monte Carlo is used to draw samples of the posterior probability density function of the structure model parameters as well as the uncertain prediction variances. The different levels of modeling uncertainty and complexity are modeled through three FE models, including a true model, a model with more complexity, and a model with modeling error. Bayesian updating is performed for the three FE models considering the three aforementioned treatments of the prediction error variances. The effect of number of measurements on the model updating performance is also examined in the study. The results are compared based on model class assessment and indicate that updating the prediction error variances as uncertain parameters at the model

Worm Phenotype Ontology: Integrating phenotype data within and beyond the C. elegans community

Directory of Open Access Journals (Sweden)

Yook Karen

2011-01-01

Full Text Available Abstract Background Caenorhabditis elegans gene-based phenotype information dates back to the 1970's, beginning with Sydney Brenner and the characterization of behavioral and morphological mutant alleles via classical genetics in order to understand nervous system function. Since then C. elegans has become an important genetic model system for the study of basic biological and biomedical principles, largely through the use of phenotype analysis. Because of the growth of C. elegans as a genetically tractable model organism and the development of large-scale analyses, there has been a significant increase of phenotype data that needs to be managed and made accessible to the research community. To do so, a standardized vocabulary is necessary to integrate phenotype data from diverse sources, permit integration with other data types and render the data in a computable form. Results We describe a hierarchically structured, controlled vocabulary of terms that can be used to standardize phenotype descriptions in C. elegans, namely the Worm Phenotype Ontology (WPO. The WPO is currently comprised of 1,880 phenotype terms, 74% of which have been used in the annotation of phenotypes associated with greater than 18,000 C. elegans genes. The scope of the WPO is not exclusively limited to C. elegans biology, rather it is devised to also incorporate phenotypes observed in related nematode species. We have enriched the value of the WPO by integrating it with other ontologies, thereby increasing the accessibility of worm phenotypes to non-nematode biologists. We are actively developing the WPO to continue to fulfill the evolving needs of the scientific community and hope to engage researchers in this crucial endeavor. Conclusions We provide a phenotype ontology (WPO that will help to facilitate data retrieval, and cross-species comparisons within the nematode community. In the larger scientific community, the WPO will permit data integration, and

Using whole-genome sequence data to predict quantitative trait phenotypes in Drosophila melanogaster.

Directory of Open Access Journals (Sweden)

Ulrike Ober

Full Text Available Predicting organismal phenotypes from genotype data is important for plant and animal breeding, medicine, and evolutionary biology. Genomic-based phenotype prediction has been applied for single-nucleotide polymorphism (SNP genotyping platforms, but not using complete genome sequences. Here, we report genomic prediction for starvation stress resistance and startle response in Drosophila melanogaster, using ∼2.5 million SNPs determined by sequencing the Drosophila Genetic Reference Panel population of inbred lines. We constructed a genomic relationship matrix from the SNP data and used it in a genomic best linear unbiased prediction (GBLUP model. We assessed predictive ability as the correlation between predicted genetic values and observed phenotypes by cross-validation, and found a predictive ability of 0.239±0.008 (0.230±0.012 for starvation resistance (startle response. The predictive ability of BayesB, a Bayesian method with internal SNP selection, was not greater than GBLUP. Selection of the 5% SNPs with either the highest absolute effect or variance explained did not improve predictive ability. Predictive ability decreased only when fewer than 150,000 SNPs were used to construct the genomic relationship matrix. We hypothesize that predictive power in this population stems from the SNP-based modeling of the subtle relationship structure caused by long-range linkage disequilibrium and not from population structure or SNPs in linkage disequilibrium with causal variants. We discuss the implications of these results for genomic prediction in other organisms.

A characterization of optimal portfolios under the tail mean-variance criterion

OpenAIRE

Owadally, I.; Landsman, Z.

2013-01-01

The tail mean–variance model was recently introduced for use in risk management and portfolio choice; it involves a criterion that focuses on the risk of rare but large losses, which is particularly important when losses have heavy-tailed distributions. If returns or losses follow a multivariate elliptical distribution, the use of risk measures that satisfy certain well-known properties is equivalent to risk management in the classical mean–variance framework. The tail mean–variance criterion...

Gender variance in childhood and sexual orientation in adulthood: a prospective study.

Science.gov (United States)

Steensma, Thomas D; van der Ende, Jan; Verhulst, Frank C; Cohen-Kettenis, Peggy T

2013-11-01

Several retrospective and prospective studies have reported on the association between childhood gender variance and sexual orientation and gender discomfort in adulthood. In most of the retrospective studies, samples were drawn from the general population. The samples in the prospective studies consisted of clinically referred children. In understanding the extent to which the association applies for the general population, prospective studies using random samples are needed. This prospective study examined the association between childhood gender variance, and sexual orientation and gender discomfort in adulthood in the general population. In 1983, we measured childhood gender variance, in 406 boys and 473 girls. In 2007, sexual orientation and gender discomfort were assessed. Childhood gender variance was measured with two items from the Child Behavior Checklist/4-18. Sexual orientation was measured for four parameters of sexual orientation (attraction, fantasy, behavior, and identity). Gender discomfort was assessed by four questions (unhappiness and/or uncertainty about one's gender, wish or desire to be of the other gender, and consideration of living in the role of the other gender). For both men and women, the presence of childhood gender variance was associated with homosexuality for all four parameters of sexual orientation, but not with bisexuality. The report of adulthood homosexuality was 8 to 15 times higher for participants with a history of gender variance (10.2% to 12.2%), compared to participants without a history of gender variance (1.2% to 1.7%). The presence of childhood gender variance was not significantly associated with gender discomfort in adulthood. This study clearly showed a significant association between childhood gender variance and a homosexual sexual orientation in adulthood in the general population. In contrast to the findings in clinically referred gender-variant children, the presence of a homosexual sexual orientation in

29 CFR 1926.2 - Variances from safety and health standards.

Science.gov (United States)

2010-07-01

... from safety and health standards. (a) Variances from standards which are, or may be, published in this... 29 Labor 8 2010-07-01 2010-07-01 false Variances from safety and health standards. 1926.2 Section 1926.2 Labor Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION...

Association of genetic and phenotypic variability with geography and climate in three southern California oaks.

Science.gov (United States)

Riordan, Erin C; Gugger, Paul F; Ortego, Joaquín; Smith, Carrie; Gaddis, Keith; Thompson, Pam; Sork, Victoria L

2016-01-01

Geography and climate shape the distribution of organisms, their genotypes, and their phenotypes. To understand historical and future evolutionary and ecological responses to climate, we compared the association of geography and climate of three oak species (Quercus engelmannii, Quercus berberidifolia, and Quercus cornelius-mulleri) in an environmentally heterogeneous region of southern California at three organizational levels: regional species distributions, genetic variation, and phenotypic variation. We identified climatic variables influencing regional distribution patterns using species distribution models (SDMs), and then tested whether those individual variables are important in shaping genetic (microsatellite) and phenotypic (leaf morphology) variation. We estimated the relative contributions of geography and climate using multivariate redundancy analyses (RDA) with variance partitioning. The modeled distribution of each species was influenced by climate differently. Our analysis of genetic variation using RDA identified small but significant associations between genetic variation with climate and geography in Q. engelmannii and Q. cornelius-mulleri, but not in Q. berberidifolia, and climate explained more of the variation. Our analysis of phenotypic variation in Q. engelmannii indicated that climate had more impact than geography, but not in Q. berberidifolia. Throughout our analyses, we did not find a consistent pattern in effects of individual climatic variables. Our comparative analysis illustrates that climate influences tree response at all organizational levels, but the important climate factors vary depending on the level and on the species. Because of these species-specific and level-specific responses, today's sympatric species are unlikely to have similar distributions in the future. © 2016 Botanical Society of America.

Allowing variance may enlarge the safe operating space for exploited ecosystems.

Science.gov (United States)

Carpenter, Stephen R; Brock, William A; Folke, Carl; van Nes, Egbert H; Scheffer, Marten

2015-11-17

Variable flows of food, water, or other ecosystem services complicate planning. Management strategies that decrease variability and increase predictability may therefore be preferred. However, actions to decrease variance over short timescales (2-4 y), when applied continuously, may lead to long-term ecosystem changes with adverse consequences. We investigated the effects of managing short-term variance in three well-understood models of ecosystem services: lake eutrophication, harvest of a wild population, and yield of domestic herbivores on a rangeland. In all cases, actions to decrease variance can increase the risk of crossing critical ecosystem thresholds, resulting in less desirable ecosystem states. Managing to decrease short-term variance creates ecosystem fragility by changing the boundaries of safe operating spaces, suppressing information needed for adaptive management, cancelling signals of declining resilience, and removing pressures that may build tolerance of stress. Thus, the management of variance interacts strongly and inseparably with the management of resilience. By allowing for variation, learning, and flexibility while observing change, managers can detect opportunities and problems as they develop while sustaining the capacity to deal with them.

Temperature variance study in Monte-Carlo photon transport theory

International Nuclear Information System (INIS)

Giorla, J.

1985-10-01

We study different Monte-Carlo methods for solving radiative transfer problems, and particularly Fleck's Monte-Carlo method. We first give the different time-discretization schemes and the corresponding stability criteria. Then we write the temperature variance as a function of the variances of temperature and absorbed energy at the previous time step. Finally we obtain some stability criteria for the Monte-Carlo method in the stationary case [fr

Syndromic (phenotypic diarrhea in early infancy

Directory of Open Access Journals (Sweden)

Bodemer Christine

2008-02-01

Full Text Available Abstract Syndromic diarrhea (SD, also known as phenotypic diarrhea (PD or tricho-hepato-enteric syndrome (THE, is a congenital enteropathy presenting with early-onset of severe diarrhea requiring parenteral nutrition (PN. To date, no epidemiological data are available. The estimated prevalence is approximately 1/300,000–400,000 live births in Western Europe. Ethnic origin does not appear to be associated with SD. Infants are born small for gestational age and present with facial dysmorphism including prominent forehead and cheeks, broad nasal root and hypertelorism. Hairs are woolly, easily removed and poorly pigmented. Severe and persistent diarrhea starts within the first 6 months of life (≤ 1 month in most cases and is accompanied by severe malabsorption leading to early and relentless protein energy malnutrition with failure to thrive. Liver disease affects about half of patients with extensive fibrosis or cirrhosis. There is currently no specific biochemical profile, though a functional T-cell immune deficiency with defective antibody production was reported. Microscopic analysis of the hair show twisted hair (pili torti, aniso- and poilkilotrichosis, and trichorrhexis nodosa. Histopathological analysis of small intestine biopsy shows non-specific villous atrophy with low or no mononuclear cell infiltration of the lamina propria, and no specific histological abnormalities involving the epithelium. The etiology remains unknown. The frequent association of the disorder with parental consanguinity and/or affected siblings suggests a genetic origin with an autosomal recessive mode of transmission. Early management consists of total PN. Some infants have a rather milder phenotype with partial PN dependency or require only enteral feeding. Prognosis of this syndrome is poor, but most patients now survive, and about half of the patients may be weaned from PN at adolescence, but experience failure to thrive and final short stature. Disease name

Estimation of Total Error in DWPF Reported Radionuclide Inventories

International Nuclear Information System (INIS)

Edwards, T.B.

1995-01-01

This report investigates the impact of random errors due to measurement and sampling on the reported concentrations of radionuclides in DWPF's filled canister inventory resulting from each macro-batch. The objective of this investigation is to estimate the variance of the total error in reporting these radionuclide concentrations

Study of the variance of a Monte Carlo calculation. Application to weighting; Etude de la variance d'un calcul de Monte Carlo. Application a la ponderation

Energy Technology Data Exchange (ETDEWEB)

Lanore, Jeanne-Marie [Commissariat a l' Energie Atomique - CEA, Centre d' Etudes Nucleaires de Fontenay-aux-Roses, Direction des Piles Atomiques, Departement des Etudes de Piles, Service d' Etudes de Protections de Piles (France)

1969-04-15

One of the main difficulties in Monte Carlo computations is the estimation of the results variance. Generally, only an apparent variance can be observed over a few calculations, often very different from the actual variance. By studying a large number of short calculations, the authors have tried to evaluate the real variance, and then to apply the obtained results to the optimization of the computations. The program used is the Poker one-dimensional Monte Carlo program. Calculations are performed in two types of fictitious environments: a body with constant cross section, without absorption, where all shocks are elastic and isotropic; a body with variable cross section (presenting a very pronounced peak and hole), with an anisotropy for high energy elastic shocks, and with the possibility of inelastic shocks (this body presents all the features that can appear in a real case)

Noise-induced Min phenotypes in E. coli.

Directory of Open Access Journals (Sweden)

David Fange

2006-06-01

Full Text Available The spatiotemporal oscillations of the Escherichia coli proteins MinD and MinE direct cell division to the region between the chromosomes. Several quantitative models of the Min system have been suggested before, but no one of them accounts for the behavior of all documented mutant phenotypes. We analyzed the stochastic reaction-diffusion kinetics of the Min proteins for several E. coli mutants and compared the results to the corresponding deterministic mean-field description. We found that wild-type (wt and filamentous (ftsZ- cells are well characterized by the mean-field model, but that a stochastic model is necessary to account for several of the characteristics of the spherical (rodA- and phospathedylethanolamide-deficient (PE- phenotypes. For spherical cells, the mean-field model is bistable, and the system can get trapped in a non-oscillatory state. However, when the intrinsic noise is considered, only the experimentally observed oscillatory behavior remains. The stochastic model also reproduces the change in oscillation directions observed in the spherical phenotype and the occasional gliding of the MinD region along the inner membrane. For the PE- mutant, the stochastic model explains the appearance of randomly localized and dense MinD clusters as a nucleation phenomenon, in which the stochastic kinetics at low copy number causes local discharges of the high MinD(ATP to MinD(ADP potential. We find that a simple five-reaction model of the Min system can explain all documented Min phenotypes, if stochastic kinetics and three-dimensional diffusion are accounted for. Our results emphasize that local copy number fluctuation may result in phenotypic differences although the total number of molecules of the relevant species is high.

Adjustment of heterogenous variances and a calving year effect in ...

African Journals Online (AJOL)

Data at the beginning and at the end of lactation period, have higher variances than tests in the middle of the lactation. Furthermore, first lactations have lower mean and variances compared to second and third lactations. This is a deviation from the basic assumptions required for the application of repeatability models.

Estimating Predictive Variance for Statistical Gas Distribution Modelling

International Nuclear Information System (INIS)

Lilienthal, Achim J.; Asadi, Sahar; Reggente, Matteo

2009-01-01

Recent publications in statistical gas distribution modelling have proposed algorithms that model mean and variance of a distribution. This paper argues that estimating the predictive concentration variance entails not only a gradual improvement but is rather a significant step to advance the field. This is, first, since the models much better fit the particular structure of gas distributions, which exhibit strong fluctuations with considerable spatial variations as a result of the intermittent character of gas dispersal. Second, because estimating the predictive variance allows to evaluate the model quality in terms of the data likelihood. This offers a solution to the problem of ground truth evaluation, which has always been a critical issue for gas distribution modelling. It also enables solid comparisons of different modelling approaches, and provides the means to learn meta parameters of the model, to determine when the model should be updated or re-initialised, or to suggest new measurement locations based on the current model. We also point out directions of related ongoing or potential future research work.

Genetic and phenotypic variation along an ecological gradient in lake trout Salvelinus namaycush

Science.gov (United States)

Baillie, Shauna M.; Muir, Andrew M.; Hansen, Michael J.; Krueger, Charles C.; Bentzen, Paul

2016-01-01

BackgroundAdaptive radiation involving a colonizing phenotype that rapidly evolves into at least one other ecological variant, or ecotype, has been observed in a variety of freshwater fishes in post-glacial environments. However, few studies consider how phenotypic traits vary with regard to neutral genetic partitioning along ecological gradients. Here, we present the first detailed investigation of lake trout Salvelinus namaycushthat considers variation as a cline rather than discriminatory among ecotypes. Genetic and phenotypic traits organized along common ecological gradients of water depth and geographic distance provide important insights into diversification processes in a lake with high levels of human disturbance from over-fishing.ResultsFour putative lake trout ecotypes could not be distinguished using population genetic methods, despite morphological differences. Neutral genetic partitioning in lake trout was stronger along a gradient of water depth, than by locality or ecotype. Contemporary genetic migration patterns were consistent with isolation-by-depth. Historical gene flow patterns indicated colonization from shallow to deep water. Comparison of phenotypic (Pst) and neutral genetic variation (Fst) revealed that morphological traits related to swimming performance (e.g., buoyancy, pelvic fin length) departed more strongly from neutral expectations along a depth gradient than craniofacial feeding traits. Elevated phenotypic variance with increasing water depth in pelvic fin length indicated possible ongoing character release and diversification. Finally, differences in early growth rate and asymptotic fish length across depth strata may be associated with limiting factors attributable to cold deep-water environments.ConclusionWe provide evidence of reductions in gene flow and divergent natural selection associated with water depth in Lake Superior. Such information is relevant for documenting intraspecific biodiversity in the largest freshwater lake

Estimating integrated variance in the presence of microstructure noise using linear regression

Science.gov (United States)

Holý, Vladimír

2017-07-01

Using financial high-frequency data for estimation of integrated variance of asset prices is beneficial but with increasing number of observations so-called microstructure noise occurs. This noise can significantly bias the realized variance estimator. We propose a method for estimation of the integrated variance robust to microstructure noise as well as for testing the presence of the noise. Our method utilizes linear regression in which realized variances estimated from different data subsamples act as dependent variable while the number of observations act as explanatory variable. We compare proposed estimator with other methods on simulated data for several microstructure noise structures.

Impact of QTL minor allele frequency on genomic evaluation using real genotype data and simulated phenotypes in Japanese Black cattle.

Science.gov (United States)

Uemoto, Yoshinobu; Sasaki, Shinji; Kojima, Takatoshi; Sugimoto, Yoshikazu; Watanabe, Toshio

2015-11-19

Genetic variance that is not captured by single nucleotide polymorphisms (SNPs) is due to imperfect linkage disequilibrium (LD) between SNPs and quantitative trait loci (QTLs), and the extent of LD between SNPs and QTLs depends on different minor allele frequencies (MAF) between them. To evaluate the impact of MAF of QTLs on genomic evaluation, we performed a simulation study using real cattle genotype data. In total, 1368 Japanese Black cattle and 592,034 SNPs (Illumina BovineHD BeadChip) were used. We simulated phenotypes using real genotypes under different scenarios, varying the MAF categories, QTL heritability, number of QTLs, and distribution of QTL effect. After generating true breeding values and phenotypes, QTL heritability was estimated and the prediction accuracy of genomic estimated breeding value (GEBV) was assessed under different SNP densities, prediction models, and population size by a reference-test validation design. The extent of LD between SNPs and QTLs in this population was higher in the QTLs with high MAF than in those with low MAF. The effect of MAF of QTLs depended on the genetic architecture, evaluation strategy, and population size in genomic evaluation. In genetic architecture, genomic evaluation was affected by the MAF of QTLs combined with the QTL heritability and the distribution of QTL effect. The number of QTL was not affected on genomic evaluation if the number of QTL was more than 50. In the evaluation strategy, we showed that different SNP densities and prediction models affect the heritability estimation and genomic prediction and that this depends on the MAF of QTLs. In addition, accurate QTL heritability and GEBV were obtained using denser SNP information and the prediction model accounted for the SNPs with low and high MAFs. In population size, a large sample size is needed to increase the accuracy of GEBV. The MAF of QTL had an impact on heritability estimation and prediction accuracy. Most genetic variance can be captured

The neuroanatomical phenotype of tuberous sclerosis complex: focus on radial migration lines

International Nuclear Information System (INIS)

Eeghen, Agnies M. van; Teran, Laura Ortiz; Johnson, Jason; Caruso, Paul; Pulsifer, Margaret B.; Thiele, Elizabeth A.

2013-01-01

The contribution of radial migration lines (RMLs) to the neuroanatomical and neurocognitive phenotype of tuberous sclerosis complex (TSC) is unclear. The aim of this study was to perform a comprehensive evaluation of the neuroradiological phenotype of TSC, distinguishing RMLs from normal-appearing white matter (NAWM) using diffusion tensor imaging (DTI) and volumetric fluid-attenuated inversion recovery imaging. Magnetic resonance images of 30 patients with TSC were evaluated. The frequencies of RMLs, tubers, and subependymal nodules (SENs) were determined for every hemispheric lobe. Cerebellar lesions and subependymal giant cell tumors were counted. DTI metrics were obtained from the NAWM of every hemispheric lobe and from the largest RML and tuber. Analyses of variance and correlations were performed to investigate the associations between neuroanatomical characteristics and relationships between RML frequency and neurocognitive outcomes. NAWM DTI metrics were compared with measurements of 16 control patients. A mean of 47 RMLs, 27 tubers, and 10 SENs were found per patient, and the frequencies of these lesions were strongly correlated (p < 0.001). RML fractional anisotropy and mean diffusivity were strongly inversely correlated (p = 0.003). NAWM DTI metrics were similar to the controls (p = 0.26). RML frequency was strongly associated with age of seizure onset (p = 0.003), intelligence outcomes (p = 0.01), and level of autistic features (p = 0.007). A detailed neuroradiological phenotype is presented, showing that RMLs are the most frequent neuroanatomical lesion, are responsible for white matter DTI abnormalities, and are strongly associated with age of seizure onset, intelligence outcomes, and level of autistic features. (orig.)

The neuroanatomical phenotype of tuberous sclerosis complex: focus on radial migration lines

Energy Technology Data Exchange (ETDEWEB)

Eeghen, Agnies M. van [Massachusetts General Hospital, Department of Neurology, Carol and James Herscot Center for Tuberous Sclerosis Complex, Boston, MA (United States); Erasmus Medical Centre, ENCORE, Expertise Centre for Neurodevelopmental Disorders, Department of Neuroscience, Rotterdam (Netherlands); Teran, Laura Ortiz; Johnson, Jason; Caruso, Paul [Massachusetts General Hospital, Department of Radiology, Boston, MA (United States); Pulsifer, Margaret B. [Massachusetts General Hospital, Department of Psychiatry, Psychological Assessment Center, Boston, MA (United States); Thiele, Elizabeth A. [Massachusetts General Hospital, Department of Neurology, Carol and James Herscot Center for Tuberous Sclerosis Complex, Boston, MA (United States)

2013-08-15

The contribution of radial migration lines (RMLs) to the neuroanatomical and neurocognitive phenotype of tuberous sclerosis complex (TSC) is unclear. The aim of this study was to perform a comprehensive evaluation of the neuroradiological phenotype of TSC, distinguishing RMLs from normal-appearing white matter (NAWM) using diffusion tensor imaging (DTI) and volumetric fluid-attenuated inversion recovery imaging. Magnetic resonance images of 30 patients with TSC were evaluated. The frequencies of RMLs, tubers, and subependymal nodules (SENs) were determined for every hemispheric lobe. Cerebellar lesions and subependymal giant cell tumors were counted. DTI metrics were obtained from the NAWM of every hemispheric lobe and from the largest RML and tuber. Analyses of variance and correlations were performed to investigate the associations between neuroanatomical characteristics and relationships between RML frequency and neurocognitive outcomes. NAWM DTI metrics were compared with measurements of 16 control patients. A mean of 47 RMLs, 27 tubers, and 10 SENs were found per patient, and the frequencies of these lesions were strongly correlated (p < 0.001). RML fractional anisotropy and mean diffusivity were strongly inversely correlated (p = 0.003). NAWM DTI metrics were similar to the controls (p = 0.26). RML frequency was strongly associated with age of seizure onset (p = 0.003), intelligence outcomes (p = 0.01), and level of autistic features (p = 0.007). A detailed neuroradiological phenotype is presented, showing that RMLs are the most frequent neuroanatomical lesion, are responsible for white matter DTI abnormalities, and are strongly associated with age of seizure onset, intelligence outcomes, and level of autistic features. (orig.)

Individual and collective bodies: using measures of variance and association in contextual epidemiology.

Science.gov (United States)

Merlo, J; Ohlsson, H; Lynch, K F; Chaix, B; Subramanian, S V

2009-12-01

Social epidemiology investigates both individuals and their collectives. Although the limits that define the individual bodies are very apparent, the collective body's geographical or cultural limits (eg "neighbourhood") are more difficult to discern. Also, epidemiologists normally investigate causation as changes in group means. However, many variables of interest in epidemiology may cause a change in the variance of the distribution of the dependent variable. In spite of that, variance is normally considered a measure of uncertainty or a nuisance rather than a source of substantive information. This reasoning is also true in many multilevel investigations, whereas understanding the distribution of variance across levels should be fundamental. This means-centric reductionism is mostly concerned with risk factors and creates a paradoxical situation, as social medicine is not only interested in increasing the (mean) health of the population, but also in understanding and decreasing inappropriate health and health care inequalities (variance). Critical essay and literature review. The present study promotes (a) the application of measures of variance and clustering to evaluate the boundaries one uses in defining collective levels of analysis (eg neighbourhoods), (b) the combined use of measures of variance and means-centric measures of association, and (c) the investigation of causes of health variation (variance-altering causation). Both measures of variance and means-centric measures of association need to be included when performing contextual analyses. The variance approach, a new aspect of contextual analysis that cannot be interpreted in means-centric terms, allows perspectives to be expanded.

A Mean-Variance Criterion for Economic Model Predictive Control of Stochastic Linear Systems

DEFF Research Database (Denmark)

Sokoler, Leo Emil; Dammann, Bernd; Madsen, Henrik

2014-01-01

, the tractability of the resulting optimal control problem is addressed. We use a power management case study to compare different variations of the mean-variance strategy with EMPC based on the certainty equivalence principle. The certainty equivalence strategy is much more computationally efficient than the mean......-variance strategies, but it does not account for the variance of the uncertain parameters. Openloop simulations suggest that a single-stage mean-variance approach yields a significantly lower operating cost than the certainty equivalence strategy. In closed-loop, the single-stage formulation is overly conservative...... be modified to perform almost as well as the two-stage mean-variance formulation. Nevertheless, we argue that the mean-variance approach can be used both as a strategy for evaluating less computational demanding methods such as the certainty equivalence method, and as an individual control strategy when...

Investigating the minimum achievable variance in a Monte Carlo criticality calculation

Energy Technology Data Exchange (ETDEWEB)

Christoforou, Stavros; Eduard Hoogenboom, J. [Delft University of Technology, Mekelweg 15, 2629 JB Delft (Netherlands)

2008-07-01

The sources of variance in a Monte Carlo criticality calculation are identified and their contributions analyzed. A zero-variance configuration is initially simulated using analytically calculated adjoint functions for biasing. From there, the various sources are analyzed. It is shown that the minimum threshold comes from the fact that the fission source is approximated. In addition, the merits of a simple variance reduction method, such as implicit capture, are shown when compared to an analog simulation. Finally, it is shown that when non-exact adjoint functions are used for biasing, the variance reduction is rather insensitive to the quality of the adjoints, suggesting that the generation of the adjoints should have as low CPU cost as possible, in order to o et the CPU cost in the implementation of the biasing of a simulation. (authors)

Automatic Bayes Factors for Testing Equality- and Inequality-Constrained Hypotheses on Variances.

Science.gov (United States)

Böing-Messing, Florian; Mulder, Joris

2018-05-03

In comparing characteristics of independent populations, researchers frequently expect a certain structure of the population variances. These expectations can be formulated as hypotheses with equality and/or inequality constraints on the variances. In this article, we consider the Bayes factor for testing such (in)equality-constrained hypotheses on variances. Application of Bayes factors requires specification of a prior under every hypothesis to be tested. However, specifying subjective priors for variances based on prior information is a difficult task. We therefore consider so-called automatic or default Bayes factors. These methods avoid the need for the user to specify priors by using information from the sample data. We present three automatic Bayes factors for testing variances. The first is a Bayes factor with equal priors on all variances, where the priors are specified automatically using a small share of the information in the sample data. The second is the fractional Bayes factor, where a fraction of the likelihood is used for automatic prior specification. The third is an adjustment of the fractional Bayes factor such that the parsimony of inequality-constrained hypotheses is properly taken into account. The Bayes factors are evaluated by investigating different properties such as information consistency and large sample consistency. Based on this evaluation, it is concluded that the adjusted fractional Bayes factor is generally recommendable for testing equality- and inequality-constrained hypotheses on variances.

The phenotypic diversity and fruit characterization of winter squash ...

African Journals Online (AJOL)

PRECIOUS

2010-01-11

Jan 11, 2010 ... collected from different provinces of the Black Sea region in 2006 and 2007 and phenotypic ... Picture of the diversity fruit size, shape and color for Cucurbita maxima ... Fruit traits used winter squash (C. maxima Duch) population characterization. S/N ..... Group J: There were a total of 18 populations in this.

Analysis of genetic distance between Peruvian Alpaca (Vicugna Pacos showing two distinct fleece phenotypes, Suri and Huacaya, by means of microsatellite markers

Directory of Open Access Journals (Sweden)

Carlo Renieri

2011-10-01

Full Text Available Two coat phenotypes exist in Alpaca, Huacaya and Suri. The two coats show different fleece structure, textile characteristics and prices on the market. Although present scientific knowledge suggests a simple genetic model of inheritance, there is a tendency to manage and consider the two phenotypes as two different breeds. A 13 microsatellite panel was used in this study to assess genetic distance between Suri and Huacaya alpacas in a sample of non-related animals from two phenotypically pure flocks at the Illpa-Puno experimental station in Quimsachata, Peru. The animals are part of a germplasm established approximately 20 years ago and have been bred separately according to their coat type since then. Genetic variability parameters were also calculated. The data were statistically analyzed using the software Genalex 6.3, Phylip 3.69 and Fstat 2.9.3.2. The sample was tested for Hardy-Weinberg equilibrium (HWE and after strict Bonferroni correction only one locus (LCA37 showed deviation from equilibrium (Ploci associations showed significant disequilibrium. Observed heterozygosis (Ho= 0.766; SE=0.044, expected heterozygosis (He=0.769; SE=0.033, number of alleles (Na=9.667, SE=0.772 and Fixation index (F=0.004; SE=0.036 are comparable to data from previous studies. Measures of genetic distance were 0.06 for Nei’s and 0.03 for Cavalli-Sforza’s. The analysis of molecular variance reported no existing variance between populations. Considering the origin of the animals, their post domestication evolution and the reproductive practices in place, the results do not show genetic differentiation between the two populations for the studied loci.

UV spectral fingerprinting and analysis of variance-principal component analysis: a useful tool for characterizing sources of variance in plant materials.

Science.gov (United States)

Luthria, Devanand L; Mukhopadhyay, Sudarsan; Robbins, Rebecca J; Finley, John W; Banuelos, Gary S; Harnly, James M

2008-07-23

UV spectral fingerprints, in combination with analysis of variance-principal components analysis (ANOVA-PCA), can differentiate between cultivars and growing conditions (or treatments) and can be used to identify sources of variance. Broccoli samples, composed of two cultivars, were grown under seven different conditions or treatments (four levels of Se-enriched irrigation waters, organic farming, and conventional farming with 100 and 80% irrigation based on crop evaporation and transpiration rate). Freeze-dried powdered samples were extracted with methanol-water (60:40, v/v) and analyzed with no prior separation. Spectral fingerprints were acquired for the UV region (220-380 nm) using a 50-fold dilution of the extract. ANOVA-PCA was used to construct subset matrices that permitted easy verification of the hypothesis that cultivar and treatment contributed to a difference in the chemical expression of the broccoli. The sums of the squares of the same matrices were used to show that cultivar, treatment, and analytical repeatability contributed 30.5, 68.3, and 1.2% of the variance, respectively.

Candidate Genetic Pathways for Attention-Deficit/Hyperactivity Disorder (ADHD) Show Association to Hyperactive/Impulsive Symptoms in Children With ADHD

NARCIS (Netherlands)

Bralten, Janita; Franke, Barbara; Waldman, Irwin; Rommelse, Nanda; Hartman, Catharina; Asherson, Philip; Banaschewski, Tobias; Ebstein, Richard P.; Gill, Michael; Miranda, Ana; Oades, Robert D.; Roeyers, Herbert; Rothenberger, Aribert; Sergeant, Joseph A.; Oosterlaan, Jaap; Sonuga-Barke, Edmund; Steinhausen, Hans-Christoph; Faraone, Stephen V.; Buitelaar, Jan K.; Arias-Vasquez, Alejandro

2013-01-01

Objective: Because multiple genes with small effect sizes are assumed to play a role in attention-deficit/hyperactivity disorder (ADHD) etiology, considering multiple variants within the same analysis likely increases the total explained phenotypic variance, thereby boosting the power of genetic

Candidate genetic pathways for attention-deficit/hyperactivity disorder (ADHD) show association to hyperactive/impulsive symptoms in children with ADHD

NARCIS (Netherlands)

Bralten, J.; Franke, B.; Waldman, I.D.; Rommelse, N.N.J.; Hartman, C.; Asherson, P.; Banaschewski, T.; Ebstein, R.P.; Gill, M.; Miranda, A.; Oades, R.D.; Roeyers, H.; Rothenberger, A.; Sergeant, J.A.; Oosterlaan, J.; Sonuga-Barke, E.; Steinhausen, H.C.; Faraone, S.; Buitelaar, J.K.; Arias-Vasquez, A.

2013-01-01

Objective Because multiple genes with small effect sizes are assumed to play a role in attention-deficit/hyperactivity disorder (ADHD) etiology, considering multiple variants within the same analysis likely increases the total explained phenotypic variance, thereby boosting the power of genetic

Candidate genetic pathways for attention-deficit/hyperactivity disorder (ADHD) show association to hyperactive/impulsive symptoms in children with ADHD

NARCIS (Netherlands)

Bralten, J.; Franke, B.; Waldman, I.; Rommelse, N.N.J.; Hartman, C.; Asherson, P.; Banaschewski, T.; Ebstein, R.P.; Gill, M.; Miranda, A.; Oades, R.D.; Roeyers, H.; Rothenberger, A.; Sergeant, J.A.; Oosterlaan, J.; Sonuga-Barke, E.; Steinhausen, H.C.; Faraone, S.V.; Buitelaar, J.K.; Arias Vasquez, A.

2013-01-01

OBJECTIVE: Because multiple genes with small effect sizes are assumed to play a role in attention-deficit/hyperactivity disorder (ADHD) etiology, considering multiple variants within the same analysis likely increases the total explained phenotypic variance, thereby boosting the power of genetic

Relationship among phenotypic plasticity, phenotypic fluctuations ...

Indian Academy of Sciences (India)

Prakash

changes produced by mutations. On the other hand, the .... fluorescence in bacteria and checked a possible relationship between evolution speed ... at each generation, and the fluctuation by the variance of ..... that by Eigen. 4. Microscopic approach: Gene regulation network ..... Formulation; Biopolymers 20 1013. Alon U ...

Levine's guide to SPSS for analysis of variance

CERN Document Server

Braver, Sanford L; Page, Melanie

2003-01-01

A greatly expanded and heavily revised second edition, this popular guide provides instructions and clear examples for running analyses of variance (ANOVA) and several other related statistical tests of significance with SPSS. No other guide offers the program statements required for the more advanced tests in analysis of variance. All of the programs in the book can be run using any version of SPSS, including versions 11 and 11.5. A table at the end of the preface indicates where each type of analysis (e.g., simple comparisons) can be found for each type of design (e.g., mixed two-factor desi

Asthma phenotypes in childhood.

Science.gov (United States)

Reddy, Monica B; Covar, Ronina A

2016-04-01

This review describes the literature over the past 18 months that evaluated childhood asthma phenotypes, highlighting the key aspects of these studies, and comparing these studies to previous ones in this area. Recent studies on asthma phenotypes have identified new phenotypes on the basis of statistical analyses (using cluster analysis and latent class analysis methodology) and have evaluated the outcomes and associated risk factors of previously established early childhood asthma phenotypes that are based on asthma onset and patterns of wheezing illness. There have also been investigations focusing on immunologic, physiologic, and genetic correlates of various phenotypes, as well as identification of subphenotypes of severe childhood asthma. Childhood asthma remains a heterogeneous condition, and investigations into these various presentations, risk factors, and outcomes are important since they can offer therapeutic and prognostic relevance. Further investigation into the immunopathology and genetic basis underlying childhood phenotypes is important so therapy can be tailored accordingly.

Phenotypic selection in natural populations: what limits directional selection?

Science.gov (United States)

Kingsolver, Joel G; Diamond, Sarah E

2011-03-01

Studies of phenotypic selection document directional selection in many natural populations. What factors reduce total directional selection and the cumulative evolutionary responses to selection? We combine two data sets for phenotypic selection, representing more than 4,600 distinct estimates of selection from 143 studies, to evaluate the potential roles of fitness trade-offs, indirect (correlated) selection, temporally varying selection, and stabilizing selection for reducing net directional selection and cumulative responses to selection. We detected little evidence that trade-offs among different fitness components reduced total directional selection in most study systems. Comparisons of selection gradients and selection differentials suggest that correlated selection frequently reduced total selection on size but not on other types of traits. The direction of selection on a trait often changes over time in many temporally replicated studies, but these fluctuations have limited impact in reducing cumulative directional selection in most study systems. Analyses of quadratic selection gradients indicated stabilizing selection on body size in at least some studies but provided little evidence that stabilizing selection is more common than disruptive selection for most traits or study systems. Our analyses provide little evidence that fitness trade-offs, correlated selection, or stabilizing selection strongly constrains the directional selection reported for most quantitative traits.

A load factor based mean-variance analysis for fuel diversification

Energy Technology Data Exchange (ETDEWEB)

Gotham, Douglas; Preckel, Paul; Ruangpattana, Suriya [State Utility Forecasting Group, Purdue University, West Lafayette, IN (United States); Muthuraman, Kumar [McCombs School of Business, University of Texas, Austin, TX (United States); Rardin, Ronald [Department of Industrial Engineering, University of Arkansas, Fayetteville, AR (United States)

2009-03-15

Fuel diversification implies the selection of a mix of generation technologies for long-term electricity generation. The goal is to strike a good balance between reduced costs and reduced risk. The method of analysis that has been advocated and adopted for such studies is the mean-variance portfolio analysis pioneered by Markowitz (Markowitz, H., 1952. Portfolio selection. Journal of Finance 7(1) 77-91). However the standard mean-variance methodology, does not account for the ability of various fuels/technologies to adapt to varying loads. Such analysis often provides results that are easily dismissed by regulators and practitioners as unacceptable, since load cycles play critical roles in fuel selection. To account for such issues and still retain the convenience and elegance of the mean-variance approach, we propose a variant of the mean-variance analysis using the decomposition of the load into various types and utilizing the load factors of each load type. We also illustrate the approach using data for the state of Indiana and demonstrate the ability of the model in providing useful insights. (author)

Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling

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Anna A. Igolkina

2018-06-01

Full Text Available Schizophrenia (SCZ is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells. Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70 by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology

The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data

NARCIS (Netherlands)

Kohler, S.; Doelken, S.C.; Mungall, C.J.; Bauer, S.; Firth, H.V.; Bailleul-Forestier, I.; Black, G.C.M.; Brown, D.L.; Brudno, M.; Campbell, J.; FitzPatrick, D.R.; Eppig, J.T.; Jackson, A.P.; Freson, K.; Girdea, M.; Helbig, I.; Hurst, J.A.; Jahn, J.; Jackson, L.G.; Kelly, A.M.; Ledbetter, D.H.; Mansour, S.; Martin, C.L.; Moss, C.; Mumford, A.; Ouwehand, W.H.; Park, S.M.; Riggs, E.R.; Scott, R.H.; Sisodiya, S.; Vooren, S. van der; Wapner, R.J.; Wilkie, A.O.; Wright, C.F.; Silfhout, A.T. van; Leeuw, N. de; Vries, B. de; Washingthon, N.L.; Smith, C.L.; Westerfield, M.; Schofield, P.; Ruef, B.J.; Gkoutos, G.V.; Haendel, M.; Smedley, D.; Lewis, S.E.; Robinson, P.N.

2014-01-01

The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have

Mixed emotions: Sensitivity to facial variance in a crowd of faces.

Science.gov (United States)

Haberman, Jason; Lee, Pegan; Whitney, David

2015-01-01

The visual system automatically represents summary information from crowds of faces, such as the average expression. This is a useful heuristic insofar as it provides critical information about the state of the world, not simply information about the state of one individual. However, the average alone is not sufficient for making decisions about how to respond to a crowd. The variance or heterogeneity of the crowd--the mixture of emotions--conveys information about the reliability of the average, essential for determining whether the average can be trusted. Despite its importance, the representation of variance within a crowd of faces has yet to be examined. This is addressed here in three experiments. In the first experiment, observers viewed a sample set of faces that varied in emotion, and then adjusted a subsequent set to match the variance of the sample set. To isolate variance as the summary statistic of interest, the average emotion of both sets was random. Results suggested that observers had information regarding crowd variance. The second experiment verified that this was indeed a uniquely high-level phenomenon, as observers were unable to derive the variance of an inverted set of faces as precisely as an upright set of faces. The third experiment replicated and extended the first two experiments using method-of-constant-stimuli. Together, these results show that the visual system is sensitive to emergent information about the emotional heterogeneity, or ambivalence, in crowds of faces.

On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series.

Science.gov (United States)

Thompson, William Hedley; Fransson, Peter

2016-12-01

Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box-Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed.

Linking genotypes database with locus-specific database and genotype-phenotype correlation in phenylketonuria.

Science.gov (United States)

Wettstein, Sarah; Underhaug, Jarl; Perez, Belen; Marsden, Brian D; Yue, Wyatt W; Martinez, Aurora; Blau, Nenad

2015-03-01

The wide range of metabolic phenotypes in phenylketonuria is due to a large number of variants causing variable impairment in phenylalanine hydroxylase function. A total of 834 phenylalanine hydroxylase gene variants from the locus-specific database PAHvdb and genotypes of 4181 phenylketonuria patients from the BIOPKU database were characterized using FoldX, SIFT Blink, Polyphen-2 and SNPs3D algorithms. Obtained data was correlated with residual enzyme activity, patients' phenotype and tetrahydrobiopterin responsiveness. A descriptive analysis of both databases was compiled and an interactive viewer in PAHvdb database was implemented for structure visualization of missense variants. We found a quantitative relationship between phenylalanine hydroxylase protein stability and enzyme activity (r(s) = 0.479), between protein stability and allelic phenotype (r(s) = -0.458), as well as between enzyme activity and allelic phenotype (r(s) = 0.799). Enzyme stability algorithms (FoldX and SNPs3D), allelic phenotype and enzyme activity were most powerful to predict patients' phenotype and tetrahydrobiopterin response. Phenotype prediction was most accurate in deleterious genotypes (≈ 100%), followed by homozygous (92.9%), hemizygous (94.8%), and compound heterozygous genotypes (77.9%), while tetrahydrobiopterin response was correctly predicted in 71.0% of all cases. To our knowledge this is the largest study using algorithms for the prediction of patients' phenotype and tetrahydrobiopterin responsiveness in phenylketonuria patients, using data from the locus-specific and genotypes database.

Variance Swap Replication: Discrete or Continuous?

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Fabien Le Floc’h

2018-02-01

Full Text Available The popular replication formula to price variance swaps assumes continuity of traded option strikes. In practice, however, there is only a discrete set of option strikes traded on the market. We present here different discrete replication strategies and explain why the continuous replication price is more relevant.

Impact of Damping Uncertainty on SEA Model Response Variance

Science.gov (United States)

Schiller, Noah; Cabell, Randolph; Grosveld, Ferdinand

2010-01-01

Statistical Energy Analysis (SEA) is commonly used to predict high-frequency vibroacoustic levels. This statistical approach provides the mean response over an ensemble of random subsystems that share the same gross system properties such as density, size, and damping. Recently, techniques have been developed to predict the ensemble variance as well as the mean response. However these techniques do not account for uncertainties in the system properties. In the present paper uncertainty in the damping loss factor is propagated through SEA to obtain more realistic prediction bounds that account for both ensemble and damping variance. The analysis is performed on a floor-equipped cylindrical test article that resembles an aircraft fuselage. Realistic bounds on the damping loss factor are determined from measurements acquired on the sidewall of the test article. The analysis demonstrates that uncertainties in damping have the potential to significantly impact the mean and variance of the predicted response.

The Impact of Jump Distributions on the Implied Volatility of Variance

DEFF Research Database (Denmark)

Nicolato, Elisa; Pisani, Camilla; Pedersen, David Sloth

2017-01-01

We consider a tractable affine stochastic volatility model that generalizes the seminal Heston (1993) model by augmenting it with jumps in the instantaneous variance process. In this framework, we consider both realized variance options and VIX options, and we examine the impact of the distribution...... of jumps on the associated implied volatility smile. We provide sufficient conditions for the asymptotic behavior of the implied volatility of variance for small and large strikes. In particular, by selecting alternative jump distributions, we show that one can obtain fundamentally different shapes...

Assessing the value of phenotypic information from non-genotyped animals for QTL mapping of complex traits in real and simulated populations.

Science.gov (United States)

Melo, Thaise P; Takada, Luciana; Baldi, Fernando; Oliveira, Henrique N; Dias, Marina M; Neves, Haroldo H R; Schenkel, Flavio S; Albuquerque, Lucia G; Carvalheiro, Roberto

2016-06-21

QTL mapping through genome-wide association studies (GWAS) is challenging, especially in the case of low heritability complex traits and when few animals possess genotypic and phenotypic information. When most of the phenotypic information is from non-genotyped animals, GWAS can be performed using the weighted single-step GBLUP (WssGBLUP) method, which permits to combine all available information, even that of non-genotyped animals. However, it is not clear to what extent phenotypic information from non-genotyped animals increases the power of QTL detection, and whether factors such as the extent of linkage disequilibrium (LD) in the population and weighting SNPs in WssGBLUP affect the importance of using information from non-genotyped animals in GWAS. These questions were investigated in this study using real and simulated data. Analysis of real data showed that the use of phenotypes of non-genotyped animals affected SNP effect estimates and, consequently, QTL mapping. Despite some coincidence, the most important genomic regions identified by the analyses, either using or ignoring phenotypes of non-genotyped animals, were not the same. The simulation results indicated that the inclusion of all available phenotypic information, even that of non-genotyped animals, tends to improve QTL detection for low heritability complex traits. For populations with low levels of LD, this trend of improvement was less pronounced. Stronger shrinkage on SNPs explaining lower variance was not necessarily associated with better QTL mapping. The use of phenotypic information from non-genotyped animals in GWAS may improve the ability to detect QTL for low heritability complex traits, especially in populations in which the level of LD is high.

Replication Variance Estimation under Two-phase Sampling in the Presence of Non-response

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Muqaddas Javed

2014-09-01

Full Text Available Kim and Yu (2011 discussed replication variance estimator for two-phase stratified sampling. In this paper estimators for mean have been proposed in two-phase stratified sampling for different situation of existence of non-response at first phase and second phase. The expressions of variances of these estimators have been derived. Furthermore, replication-based jackknife variance estimators of these variances have also been derived. Simulation study has been conducted to investigate the performance of the suggested estimators.

Thermospheric mass density model error variance as a function of time scale

Science.gov (United States)

Emmert, J. T.; Sutton, E. K.

2017-12-01

In the increasingly crowded low-Earth orbit environment, accurate estimation of orbit prediction uncertainties is essential for collision avoidance. Poor characterization of such uncertainty can result in unnecessary and costly avoidance maneuvers (false positives) or disregard of a collision risk (false negatives). Atmospheric drag is a major source of orbit prediction uncertainty, and is particularly challenging to account for because it exerts a cumulative influence on orbital trajectories and is therefore not amenable to representation by a single uncertainty parameter. To address this challenge, we examine the variance of measured accelerometer-derived and orbit-derived mass densities with respect to predictions by thermospheric empirical models, using the data-minus-model variance as a proxy for model uncertainty. Our analysis focuses mainly on the power spectrum of the residuals, and we construct an empirical model of the variance as a function of time scale (from 1 hour to 10 years), altitude, and solar activity. We find that the power spectral density approximately follows a power-law process but with an enhancement near the 27-day solar rotation period. The residual variance increases monotonically with altitude between 250 and 550 km. There are two components to the variance dependence on solar activity: one component is 180 degrees out of phase (largest variance at solar minimum), and the other component lags 2 years behind solar maximum (largest variance in the descending phase of the solar cycle).

Toward automatic phenotyping of retinal images from genetically determined mono- and dizygotic twins using amplitude modulation-frequency modulation methods

Science.gov (United States)

Soliz, P.; Davis, B.; Murray, V.; Pattichis, M.; Barriga, S.; Russell, S.

2010-03-01

This paper presents an image processing technique for automatically categorize age-related macular degeneration (AMD) phenotypes from retinal images. Ultimately, an automated approach will be much more precise and consistent in phenotyping of retinal diseases, such as AMD. We have applied the automated phenotyping to retina images from a cohort of mono- and dizygotic twins. The application of this technology will allow one to perform more quantitative studies that will lead to a better understanding of the genetic and environmental factors associated with diseases such as AMD. A method for classifying retinal images based on features derived from the application of amplitude-modulation frequency-modulation (AM-FM) methods is presented. Retinal images from identical and fraternal twins who presented with AMD were processed to determine whether AM-FM could be used to differentiate between the two types of twins. Results of the automatic classifier agreed with the findings of other researchers in explaining the variation of the disease between the related twins. AM-FM features classified 72% of the twins correctly. Visual grading found that genetics could explain between 46% and 71% of the variance.

Kriging with Unknown Variance Components for Regional Ionospheric Reconstruction

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Ling Huang

2017-02-01

Full Text Available Ionospheric delay effect is a critical issue that limits the accuracy of precise Global Navigation Satellite System (GNSS positioning and navigation for single-frequency users, especially in mid- and low-latitude regions where variations in the ionosphere are larger. Kriging spatial interpolation techniques have been recently introduced to model the spatial correlation and variability of ionosphere, which intrinsically assume that the ionosphere field is stochastically stationary but does not take the random observational errors into account. In this paper, by treating the spatial statistical information on ionosphere as prior knowledge and based on Total Electron Content (TEC semivariogram analysis, we use Kriging techniques to spatially interpolate TEC values. By assuming that the stochastic models of both the ionospheric signals and measurement errors are only known up to some unknown factors, we propose a new Kriging spatial interpolation method with unknown variance components for both the signals of ionosphere and TEC measurements. Variance component estimation has been integrated with Kriging to reconstruct regional ionospheric delays. The method has been applied to data from the Crustal Movement Observation Network of China (CMONOC and compared with the ordinary Kriging and polynomial interpolations with spherical cap harmonic functions, polynomial functions and low-degree spherical harmonic functions. The statistics of results indicate that the daily ionospheric variations during the experimental period characterized by the proposed approach have good agreement with the other methods, ranging from 10 to 80 TEC Unit (TECU, 1 TECU = 1 × 1016 electrons/m2 with an overall mean of 28.2 TECU. The proposed method can produce more appropriate estimations whose general TEC level is as smooth as the ordinary Kriging but with a smaller standard deviation around 3 TECU than others. The residual results show that the interpolation precision of the

A quantitative genetic analysis of intermediate asthma phenotypes

DEFF Research Database (Denmark)

Thomsen, S.F.; Ferreira, M.A.R.; Kyvik, K.O.

2009-01-01

to the observed data using maximum likelihood methods. RESULTS: Additive genetic factors explained 67% of the variation in FeNO, 43% in airway responsiveness, 22% in airway obstruction, and 81% in serum total IgE. In general, traits had genetically and environmentally distinct variance structures. The most......AIM: To study the relative contribution of genetic and environmental factors to the correlation between exhaled nitric oxide (FeNO), airway responsiveness, airway obstruction, and serum total immunoglobulin E (IgE). METHODS: Within a sampling frame of 21,162 twin subjects, 20-49 years of age, from...... substantial genetic similarity was observed between FeNO and serum total IgE, genetic correlation (rhoA) = 0.37, whereas the strongest environmental resemblance was observed between airway responsiveness and airway obstruction, specific environmental correlation (rhoE) = -0.46, and between FeNO and airway...

A quantitative genetic analysis of intermediate asthma phenotypes

DEFF Research Database (Denmark)

Thomsen, S F; Ferreira, M A R; Kyvik, K O

2009-01-01

to the observed data using maximum likelihood methods. Results: Additive genetic factors explained 67% of the variation in FeNO, 43% in airway responsiveness, 22% in airway obstruction, and 81% in serum total IgE. In general, traits had genetically and environmentally distinct variance structures. The most......Aim: To study the relative contribution of genetic and environmental factors to the correlation between exhaled nitric oxide (FeNO), airway responsiveness, airway obstruction, and serum total immunoglobulin E (IgE). Methods: Within a sampling frame of 21 162 twin subjects, 20-49 years of age, from...... substantial genetic similarity was observed between FeNO and serum total IgE, genetic correlation (rho(A)) = 0.37, whereas the strongest environmental resemblance was observed between airway responsiveness and airway obstruction, specific environmental correlation (rho(E)) = -0.46, and between FeNO and airway...

Phenotypic equilibrium as probabilistic convergence in multi-phenotype cell population dynamics.

Directory of Open Access Journals (Sweden)

Da-Quan Jiang

Full Text Available We consider the cell population dynamics with n different phenotypes. Both the Markovian branching process model (stochastic model and the ordinary differential equation (ODE system model (deterministic model are presented, and exploited to investigate the dynamics of the phenotypic proportions. We will prove that in both models, these proportions will tend to constants regardless of initial population states ("phenotypic equilibrium" under weak conditions, which explains the experimental phenomenon in Gupta et al.'s paper. We also prove that Gupta et al.'s explanation is the ODE model under a special assumption. As an application, we will give sufficient and necessary conditions under which the proportion of one phenotype tends to 0 (die out or 1 (dominate. We also extend our results to non-Markovian cases.

How the Weak Variance of Momentum Can Turn Out to be Negative

Science.gov (United States)

Feyereisen, M. R.

2015-05-01

Weak values are average quantities, therefore investigating their associated variance is crucial in understanding their place in quantum mechanics. We develop the concept of a position-postselected weak variance of momentum as cohesively as possible, building primarily on material from Moyal (Mathematical Proceedings of the Cambridge Philosophical Society, Cambridge University Press, Cambridge, 1949) and Sonego (Found Phys 21(10):1135, 1991) . The weak variance is defined in terms of the Wigner function, using a standard construction from probability theory. We show this corresponds to a measurable quantity, which is not itself a weak value. It also leads naturally to a connection between the imaginary part of the weak value of momentum and the quantum potential. We study how the negativity of the Wigner function causes negative weak variances, and the implications this has on a class of `subquantum' theories. We also discuss the role of weak variances in studying determinism, deriving the classical limit from a variational principle.

Variance gradients and uncertainty budgets for nonlinear measurement functions with independent inputs

International Nuclear Information System (INIS)

Campanelli, Mark; Kacker, Raghu; Kessel, Rüdiger

2013-01-01

A novel variance-based measure for global sensitivity analysis, termed a variance gradient (VG), is presented for constructing uncertainty budgets under the Guide to the Expression of Uncertainty in Measurement (GUM) framework for nonlinear measurement functions with independent inputs. The motivation behind VGs is the desire of metrologists to understand which inputs' variance reductions would most effectively reduce the variance of the measurand. VGs are particularly useful when the application of the first supplement to the GUM is indicated because of the inadequacy of measurement function linearization. However, VGs reduce to a commonly understood variance decomposition in the case of a linear(ized) measurement function with independent inputs for which the original GUM readily applies. The usefulness of VGs is illustrated by application to an example from the first supplement to the GUM, as well as to the benchmark Ishigami function. A comparison of VGs to other available sensitivity measures is made. (paper)

Variance in parametric images: direct estimation from parametric projections

International Nuclear Information System (INIS)

Maguire, R.P.; Leenders, K.L.; Spyrou, N.M.

2000-01-01

Recent work has shown that it is possible to apply linear kinetic models to dynamic projection data in PET in order to calculate parameter projections. These can subsequently be back-projected to form parametric images - maps of parameters of physiological interest. Critical to the application of these maps, to test for significant changes between normal and pathophysiology, is an assessment of the statistical uncertainty. In this context, parametric images also include simple integral images from, e.g., [O-15]-water used to calculate statistical parametric maps (SPMs). This paper revisits the concept of parameter projections and presents a more general formulation of the parameter projection derivation as well as a method to estimate parameter variance in projection space, showing which analysis methods (models) can be used. Using simulated pharmacokinetic image data we show that a method based on an analysis in projection space inherently calculates the mathematically rigorous pixel variance. This results in an estimation which is as accurate as either estimating variance in image space during model fitting, or estimation by comparison across sets of parametric images - as might be done between individuals in a group pharmacokinetic PET study. The method based on projections has, however, a higher computational efficiency, and is also shown to be more precise, as reflected in smooth variance distribution images when compared to the other methods. (author)

A geometric approach to multiperiod mean variance optimization of assets and liabilities

OpenAIRE

Leippold, Markus; Trojani, Fabio; Vanini, Paolo

2005-01-01

We present a geometric approach to discrete time multiperiod mean variance portfolio optimization that largely simplifies the mathematical analysis and the economic interpretation of such model settings. We show that multiperiod mean variance optimal policies can be decomposed in an orthogonal set of basis strategies, each having a clear economic interpretation. This implies that the corresponding multi period mean variance frontiers are spanned by an orthogonal basis of dynamic returns. Spec...

Mean-variance portfolio selection and efficient frontier for defined contribution pension schemes

DEFF Research Database (Denmark)

Højgaard, Bjarne; Vigna, Elena

We solve a mean-variance portfolio selection problem in the accumulation phase of a defined contribution pension scheme. The efficient frontier, which is found for the 2 asset case as well as the n + 1 asset case, gives the member the possibility to decide his own risk/reward profile. The mean...... as a mean-variance optimization problem. It is shown that the corresponding mean and variance of the final fund belong to the efficient frontier and also the opposite, that each point on the efficient frontier corresponds to a target-based optimization problem. Furthermore, numerical results indicate...... that the largely adopted lifestyle strategy seems to be very far from being efficient in the mean-variance setting....

ASYMMETRY OF MARKET RETURNS AND THE MEAN VARIANCE FRONTIER

OpenAIRE

SENGUPTA, Jati K.; PARK, Hyung S.

1994-01-01

The hypothesis that the skewness and asymmetry have no significant impact on the mean variance frontier is found to be strongly violated by monthly U.S. data over the period January 1965 through December 1974. This result raises serious doubts whether the common market portifolios such as SP 500, value weighted and equal weighted returns can serve as suitable proxies for meanvariance efficient portfolios in the CAPM framework. A new test for assessing the impact of skewness on the variance fr...

Global Gravity Wave Variances from Aura MLS: Characteristics and Interpretation

Science.gov (United States)

2008-12-01

slight longitudinal variations, with secondary high- latitude peaks occurring over Greenland and Europe . As the QBO changes to the westerly phase, the...equatorial GW temperature variances from suborbital data (e.g., Eck- ermann et al. 1995). The extratropical wave variances are generally larger in the...emanating from tropopause altitudes, presumably radiated from tropospheric jet stream in- stabilities associated with baroclinic storm systems that

A New Approach for Predicting the Variance of Random Decrement Functions

DEFF Research Database (Denmark)

Asmussen, J. C.; Brincker, Rune

mean Gaussian distributed processes the RD functions are proportional to the correlation functions of the processes. If a linear structur is loaded by Gaussian white noise the modal parameters can be extracted from the correlation funtions of the response, only. One of the weaknesses of the RD...... technique is that no consistent approach to estimate the variance of the RD functions is known. Only approximate relations are available, which can only be used under special conditions. The variance of teh RD functions contains valuable information about accuracy of the estimates. Furthermore, the variance...... can be used as basis for a decision about how many time lags from the RD funtions should be used in the modal parameter extraction procedure. This paper suggests a new method for estimating the variance of the RD functions. The method is consistent in the sense that the accuracy of the approach...

Use of genomic models to study genetic control of environmental variance

DEFF Research Database (Denmark)

Yang, Ye; Christensen, Ole Fredslund; Sorensen, Daniel

2011-01-01

. The genomic model commonly found in the literature, with marker effects affecting mean only, is extended to investigate putative effects at the level of the environmental variance. Two classes of models are proposed and their behaviour, studied using simulated data, indicates that they are capable...... of detecting genetic variation at the level of mean and variance. Implementation is via Markov chain Monte Carlo (McMC) algorithms. The models are compared in terms of a measure of global fit, in their ability to detect QTL effects and in terms of their predictive power. The models are subsequently fitted...... to back fat thickness data in pigs. The analysis of back fat thickness shows that the data support genomic models with effects on the mean but not on the variance. The relative sizes of experiment necessary to detect effects on mean and variance is discussed and an extension of the McMC algorithm...

A New Approach for Predicting the Variance of Random Decrement Functions

DEFF Research Database (Denmark)

Asmussen, J. C.; Brincker, Rune

1998-01-01

mean Gaussian distributed processes the RD functions are proportional to the correlation functions of the processes. If a linear structur is loaded by Gaussian white noise the modal parameters can be extracted from the correlation funtions of the response, only. One of the weaknesses of the RD...... technique is that no consistent approach to estimate the variance of the RD functions is known. Only approximate relations are available, which can only be used under special conditions. The variance of teh RD functions contains valuable information about accuracy of the estimates. Furthermore, the variance...... can be used as basis for a decision about how many time lags from the RD funtions should be used in the modal parameter extraction procedure. This paper suggests a new method for estimating the variance of the RD functions. The method is consistent in the sense that the accuracy of the approach...

Knowledge-based analysis of phenotypes

KAUST Repository

Hoendorf, Robert

2016-01-27

Phenotypes are the observable characteristics of an organism, and they are widely recorded in biology and medicine. To facilitate data integration, ontologies that formally describe phenotypes are being developed in several domains. I will describe a formal framework to describe phenotypes. A formalized theory of phenotypes is not only useful for domain analysis, but can also be applied to assist in the diagnosis of rare genetic diseases, and I will show how our results on the ontology of phenotypes is now applied in biomedical research.

Some novel inequalities for fuzzy variables on the variance and its rational upper bound

Directory of Open Access Journals (Sweden)

Xiajie Yi

2016-02-01

Full Text Available Abstract Variance is of great significance in measuring the degree of deviation, which has gained extensive usage in many fields in practical scenarios. The definition of the variance on the basis of the credibility measure was first put forward in 2002. Following this idea, the calculation of the accurate value of the variance for some special fuzzy variables, like the symmetric and asymmetric triangular fuzzy numbers and the Gaussian fuzzy numbers, is presented in this paper, which turns out to be far more complicated. Thus, in order to better implement variance in real-life projects like risk control and quality management, we suggest a rational upper bound of the variance based on an inequality, together with its calculation formula, which can largely simplify the calculation process within a reasonable range. Meanwhile, some discussions between the variance and its rational upper bound are presented to show the rationality of the latter. Furthermore, two inequalities regarding the rational upper bound of variance and standard deviation of the sum of two fuzzy variables and their individual variances and standard deviations are proved. Subsequently, some numerical examples are illustrated to show the effectiveness and the feasibility of the proposed inequalities.

A class of multi-period semi-variance portfolio for petroleum exploration and development

Science.gov (United States)

Guo, Qiulin; Li, Jianzhong; Zou, Caineng; Guo, Yujuan; Yan, Wei

2012-10-01

Variance is substituted by semi-variance in Markowitz's portfolio selection model. For dynamic valuation on exploration and development projects, one period portfolio selection is extended to multi-period. In this article, a class of multi-period semi-variance exploration and development portfolio model is formulated originally. Besides, a hybrid genetic algorithm, which makes use of the position displacement strategy of the particle swarm optimiser as a mutation operation, is applied to solve the multi-period semi-variance model. For this class of portfolio model, numerical results show that the mode is effective and feasible.

Bayesian evaluation of constrained hypotheses on variances of multiple independent groups

NARCIS (Netherlands)

Böing-Messing, F.; van Assen, M.A.L.M.; Hofman, A.D.; Hoijtink, H.; Mulder, J.

2017-01-01

Research has shown that independent groups often differ not only in their means, but also in their variances. Comparing and testing variances is therefore of crucial importance to understand the effect of a grouping variable on an outcome variable. Researchers may have specific expectations

Development of a treatability variance guidance document for US DOE mixed-waste streams

International Nuclear Information System (INIS)

Scheuer, N.; Spikula, R.; Harms, T.

1990-03-01

In response to the US Department of Energy's (DOE's) anticipated need for variances from the Resource Conservation and Recovery Act (RCRA) Land Disposal Restrictions (LDRs), a treatability variance guidance document was prepared. The guidance manual is for use by DOE facilities and operations offices. The manual was prepared as a part of an ongoing effort by DOE-EH to provide guidance for the operations offices and facilities to comply with the RCRA (LDRs). A treatability variance is an alternative treatment standard granted by EPA for a restricted waste. Such a variance is not an exemption from the requirements of the LDRs, but rather is an alternative treatment standard that must be met before land disposal. The manual, Guidance For Obtaining Variance From the Treatment Standards of the RCRA Land Disposal Restrictions (1), leads the reader through the process of evaluating whether a variance from the treatment standard is a viable approach and through the data-gathering and data-evaluation processes required to develop a petition requesting a variance. The DOE review and coordination process is also described and model language for use in petitions for DOE radioactive mixed waste (RMW) is provided. The guidance manual focuses on RMW streams, however the manual also is applicable to nonmixed, hazardous waste streams. 4 refs

Genetic and environmental variance and covariance parameters for some reproductive traits of Holstein and Jersey cattle in Antioquia (Colombia

Directory of Open Access Journals (Sweden)

Juan Carlos Zambrano

2014-03-01

Full Text Available The objective of this study was to estimate the genetic, phenotypic and environmental parameters for calving interval (CI, days open (DO, number of services per conception (NSC and conception rate (CR in Holstein and Jersey cattle in Antioquia (Colombia. Variance and covariance component estimates were obtained by an animal model that was solved using the derivative-free restricted maximum likelihood method. The means and standard deviations for CI, DO, NSC and CR were: 430.32±77.93 days, 127.15±76.96 days, 1.58±1.03 services per conception and 79.88±28.66% in Holstein cattle, and 409.33±86.48 days, 125.62±86.09 days, 1.48±0.98 services per conception and 84.08±27.23% in Jersey cattle, respectively. The heritability estimates (standard errors were: 0.088(0.037, 0.082(0.037, 0.040(0.025 and 0.030(0.026 in Holstein cattle and 0.072(0.098, 0.090(0.104, 0.093(0.097 and 0.147(0.117 in Jersey cattle, respectively. The results show that the genetic, phenotypic and permanent environmental correlations in the two evaluated breeds were favorable for CI × DO, CI × NSC and DO × NSC, but not for CI × CR, DO × CR and NSC × CR. Genetic and permanent environmental correlations were high in most cases in Holstein cattle, whereas in Jersey cattle they were moderate. In contrast, phenotypic correlations were very low in both breeds, except for CI × DO and NSC × CR, which were high. Overall, the genetic component found was very low (<8% in both evaluated breeds and this implies that their selection would take long time and that a good practical management of the herd will be essential in order to improve the reproductive performance.

Advanced phenotyping and phenotype data analysis for the plant growth and development study

Directory of Open Access Journals (Sweden)

Md. Matiur eRahaman

2015-08-01

Full Text Available Due to increase in the consumption of food, feed, fuel and to ensure global food security for rapidly growing human population, there is need to breed high yielding crops that can adapt to future climate. To solve these global issues, novel approaches are required to provide quantitative phenotypes to elucidate the genetic basis of agriculturally import traits and to screen germplasm with super performance in function under resource-limited environment. At present, plant phenomics has offered and integrated suite technologies for understanding the complete set of phenotypes of plants, towards the progression of the full characteristics of plants with whole sequenced genomes. In this aspect, high-throughput phenotyping platforms have been developed that enables to capture extensive and intensive phenotype data from non-destructive imaging over time. These developments advance our view on plant growth and performance with responses to the changing climate and environment. In this paper, we present a brief review on currently developed high-throughput plant phenotyping infrastructures based on imaging techniques and corresponding principles for phenotype data analysis.

Variance of a product with application to uranium estimation

International Nuclear Information System (INIS)

Lowe, V.W.; Waterman, M.S.

1976-01-01

The U in a container can either be determined directly by NDA or by estimating the weight of material in the container and the concentration of U in this material. It is important to examine the statistical properties of estimating the amount of U by multiplying the estimates of weight and concentration. The variance of the product determines the accuracy of the estimate of the amount of uranium. This paper examines the properties of estimates of the variance of the product of two random variables

Hypertriglyceridemic-waist phenotype predicts diabetes: a cohort study in Chinese urban adults

Directory of Open Access Journals (Sweden)

Zhang Meilin

2012-12-01

Full Text Available Abstract Background Hypertriglycedemic-waist (HTGW phenotype is a simple and inexpensive screening parameter to identify people at increased risk for cardiovascular disease. We evaluated whether the HTGW phenotype predicts prediabetes and diabetes in Chinese urban adults. Methods Two thousand nine hundred and eight (2908 subjects including 1957 men and 951 women, aged 20 years and older, free of prediabetes and diabetes at baseline were enrolled in 2008 and followed for 3 years. Meanwhile, new cases of prediabetes and diabetes were identified via annual physical examination. Cox proportional hazards models were used to assess the association of HTGW phenotype with the incidence of prediabetes and diabetes. Results One thousand five hundred and thirty-three (1533 new prediabetes and 90 new diabetes cases were diagnosed during the follow-up period. The accumulated incidence of prediabetes and diabetes was 52.7% and 3.1%, respectively. Compared with the normal waist normal triglyceride (NWNT group, those in the HTGW group had higher incidence of prediabetes and diabetes for both men and women. The hazard ratio (HR for developing prediabetes in the presence of HTGW phenotype at baseline was 1.51 (95% confidence interval [CI] =1.04-2.19 in women, not in men (HR=1.01; 95% CI = 0.82-1.24, after adjusting for age, body mass index, systolic blood pressure, total cholesterol and low density lipoprotein-cholesterol. The HR for developing diabetes were 4.46 (95% CI = 1.88-10.60 in men and 4.64 (95% CI = 1.20-17.97 in women for people who were HTGW phenotype at baseline, after adjusting for age, body mass index, systolic blood pressure, total cholesterol and low density lipoprotein-cholesterol. Conclusions The HTGW phenotype can be used as a simple screening approach to predict diabetes. By using this approach, it is possible to identify individuals at high-risk for diabetes, which is of great significance in reducing the incidence of diabetes among Chinese

Phenotype of normal spirometry in an aging population.

Science.gov (United States)

Vaz Fragoso, Carlos A; McAvay, Gail; Van Ness, Peter H; Casaburi, Richard; Jensen, Robert L; MacIntyre, Neil; Gill, Thomas M; Yaggi, H Klar; Concato, John

2015-10-01

In aging populations, the commonly used Global Initiative for Chronic Obstructive Lung Disease (GOLD) may misclassify normal spirometry as respiratory impairment (airflow obstruction and restrictive pattern), including the presumption of respiratory disease (chronic obstructive pulmonary disease [COPD]). To evaluate the phenotype of normal spirometry as defined by a new approach from the Global Lung Initiative (GLI), overall and across GOLD spirometric categories. Using data from COPDGene (n = 10,131; ages 45-81; smoking history, ≥10 pack-years), we evaluated spirometry and multiple phenotypes, including dyspnea severity (Modified Medical Research Council grade 0-4), health-related quality of life (St. George's Respiratory Questionnaire total score), 6-minute-walk distance, bronchodilator reversibility (FEV1 % change), computed tomography-measured percentage of lung with emphysema (% emphysema) and gas trapping (% gas trapping), and small airway dimensions (square root of the wall area for a standardized airway with an internal perimeter of 10 mm). Among 5,100 participants with GLI-defined normal spirometry, GOLD identified respiratory impairment in 1,146 (22.5%), including a restrictive pattern in 464 (9.1%), mild COPD in 380 (7.5%), moderate COPD in 302 (5.9%), and severe COPD in none. Overall, the phenotype of GLI-defined normal spirometry included normal adjusted mean values for dyspnea grade (0.8), St. George's Respiratory Questionnaire (15.9), 6-minute-walk distance (1,424 ft [434 m]), bronchodilator reversibility (2.7%), % emphysema (0.9%), % gas trapping (10.7%), and square root of the wall area for a standardized airway with an internal perimeter of 10 mm (3.65 mm); corresponding 95% confidence intervals were similarly normal. These phenotypes remained normal for GLI-defined normal spirometry across GOLD spirometric categories. GLI-defined normal spirometry, even when classified as respiratory impairment by GOLD, included adjusted mean values in the

Accounting for non-stationary variance in geostatistical mapping of soil properties

NARCIS (Netherlands)

Wadoux, Alexandre M.J.C.; Brus, Dick J.; Heuvelink, Gerard B.M.

2018-01-01

Simple and ordinary kriging assume a constant mean and variance of the soil variable of interest. This assumption is often implausible because the mean and/or variance are linked to terrain attributes, parent material or other soil forming factors. In kriging with external drift (KED)

Deep Phenotyping: Deep Learning For Temporal Phenotype/Genotype Classification

OpenAIRE

Najafi, Mohammad; Namin, Sarah; Esmaeilzadeh, Mohammad; Brown, Tim; Borevitz, Justin

2017-01-01

High resolution and high throughput, genotype to phenotype studies in plants are underway to accelerate breeding of climate ready crops. Complex developmental phenotypes are observed by imaging a variety of accessions in different environment conditions, however extracting the genetically heritable traits is challenging. In the recent years, deep learning techniques and in particular Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) and Long-Short Term Memories (LSTMs), h...

The Human Phenotype Ontology in 2017

International Nuclear Information System (INIS)

Köhler, Sebastian; Vasilevsky, Nicole A.; Engelstad, Mark; Foster, Erin; McMurry, Julie

2016-01-01

Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human PhenotypeOntology (HPO; www.human-phenotype-ontology.org) project are the phenotype vocabulary, disease-phenotype annotations and the algorithms that operate on these. These components are being used for computational deep phenotyping and precision medicine as well as integration of clinical data into translational research. The HPO is being increasingly adopted as a standard for phenotypic abnormalities by diverse groups such as international rare disease organizations, registries, clinical labs, biomedical resources, and clinical software tools and will thereby contribute toward nascent efforts at global data exchange for identifying disease etiologies. This update article reviews the progress of the HPO project since the debut Nucleic Acids Research database article in 2014, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology.

The efficiency of the crude oil markets: Evidence from variance ratio tests

Energy Technology Data Exchange (ETDEWEB)

Charles, Amelie, E-mail: acharles@audencia.co [Audencia Nantes, School of Management, 8 route de la Joneliere, 44312 Nantes (France); Darne, Olivier, E-mail: olivier.darne@univ-nantes.f [LEMNA, University of Nantes, IEMN-IAE, Chemin de la Censive du Tertre, 44322 Nantes (France)

2009-11-15

This study examines the random walk hypothesis for the crude oil markets, using daily data over the period 1982-2008. The weak-form efficient market hypothesis for two crude oil markets (UK Brent and US West Texas Intermediate) is tested with non-parametric variance ratio tests developed by [Wright J.H., 2000. Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics, 18, 1-9] and [Belaire-Franch J. and Contreras D., 2004. Ranks and signs-based multiple variance ratio tests. Working paper, Department of Economic Analysis, University of Valencia] as well as the wild-bootstrap variance ratio tests suggested by [Kim, J.H., 2006. Wild bootstrapping variance ratio tests. Economics Letters, 92, 38-43]. We find that the Brent crude oil market is weak-form efficiency while the WTI crude oil market seems to be inefficiency on the 1994-2008 sub-period, suggesting that the deregulation have not improved the efficiency on the WTI crude oil market in the sense of making returns less predictable.

The efficiency of the crude oil markets. Evidence from variance ratio tests

International Nuclear Information System (INIS)

Charles, Amelie; Darne, Olivier

2009-01-01

This study examines the random walk hypothesis for the crude oil markets, using daily data over the period 1982-2008. The weak-form efficient market hypothesis for two crude oil markets (UK Brent and US West Texas Intermediate) is tested with non-parametric variance ratio tests developed by [Wright J.H., 2000. Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics, 18, 1-9] and [Belaire-Franch J. and Contreras D., 2004. Ranks and signs-based multiple variance ratio tests. Working paper, Department of Economic Analysis, University of Valencia] as well as the wild-bootstrap variance ratio tests suggested by [Kim, J.H., 2006. Wild bootstrapping variance ratio tests. Economics Letters, 92, 38-43]. We find that the Brent crude oil market is weak-form efficiency while the WTI crude oil market seems to be inefficiency on the 1994-2008 sub-period, suggesting that the deregulation have not improved the efficiency on the WTI crude oil market in the sense of making returns less predictable. (author)

The efficiency of the crude oil markets. Evidence from variance ratio tests

Energy Technology Data Exchange (ETDEWEB)

Charles, Amelie [Audencia Nantes, School of Management, 8 route de la Joneliere, 44312 Nantes (France); Darne, Olivier [LEMNA, University of Nantes, IEMN-IAE, Chemin de la Censive du Tertre, 44322 Nantes (France)

2009-11-15

This study examines the random walk hypothesis for the crude oil markets, using daily data over the period 1982-2008. The weak-form efficient market hypothesis for two crude oil markets (UK Brent and US West Texas Intermediate) is tested with non-parametric variance ratio tests developed by [Wright J.H., 2000. Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics, 18, 1-9] and [Belaire-Franch J. and Contreras D., 2004. Ranks and signs-based multiple variance ratio tests. Working paper, Department of Economic Analysis, University of Valencia] as well as the wild-bootstrap variance ratio tests suggested by [Kim, J.H., 2006. Wild bootstrapping variance ratio tests. Economics Letters, 92, 38-43]. We find that the Brent crude oil market is weak-form efficiency while the WTI crude oil market seems to be inefficiency on the 1994-2008 sub-period, suggesting that the deregulation have not improved the efficiency on the WTI crude oil market in the sense of making returns less predictable. (author)

Hydrograph variances over different timescales in hydropower production networks

Science.gov (United States)

Zmijewski, Nicholas; Wörman, Anders

2016-08-01

The operation of water reservoirs involves a spectrum of timescales based on the distribution of stream flow travel times between reservoirs, as well as the technical, environmental, and social constraints imposed on the operation. In this research, a hydrodynamically based description of the flow between hydropower stations was implemented to study the relative importance of wave diffusion on the spectrum of hydrograph variance in a regulated watershed. Using spectral decomposition of the effluence hydrograph of a watershed, an exact expression of the variance in the outflow response was derived, as a function of the trends of hydraulic and geomorphologic dispersion and management of production and reservoirs. We show that the power spectra of involved time-series follow nearly fractal patterns, which facilitates examination of the relative importance of wave diffusion and possible changes in production demand on the outflow spectrum. The exact spectral solution can also identify statistical bounds of future demand patterns due to limitations in storage capacity. The impact of the hydraulic description of the stream flow on the reservoir discharge was examined for a given power demand in River Dalälven, Sweden, as function of a stream flow Peclet number. The regulation of hydropower production on the River Dalälven generally increased the short-term variance in the effluence hydrograph, whereas wave diffusion decreased the short-term variance over periods of white noise) as a result of current production objectives.

Variance reduction methods applied to deep-penetration problems

International Nuclear Information System (INIS)

Cramer, S.N.

1984-01-01

All deep-penetration Monte Carlo calculations require variance reduction methods. Before beginning with a detailed approach to these methods, several general comments concerning deep-penetration calculations by Monte Carlo, the associated variance reduction, and the similarities and differences of these with regard to non-deep-penetration problems will be addressed. The experienced practitioner of Monte Carlo methods will easily find exceptions to any of these generalities, but it is felt that these comments will aid the novice in understanding some of the basic ideas and nomenclature. Also, from a practical point of view, the discussions and developments presented are oriented toward use of the computer codes which are presented in segments of this Monte Carlo course

Cumulative prospect theory and mean variance analysis. A rigorous comparison

OpenAIRE

Hens, Thorsten; Mayer, Janos

2012-01-01

We compare asset allocations derived for cumulative prospect theory(CPT) based on two different methods: Maximizing CPT along the mean–variance efficient frontier and maximizing it without that restriction. We find that with normally distributed returns the difference is negligible. However, using standard asset allocation data of pension funds the difference is considerable. Moreover, with derivatives like call options the restriction to the mean-variance efficient frontier results in a siza...

Pain relief with lidocaine 5% patch in localized peripheral neuropathic pain in relation to pain phenotype

DEFF Research Database (Denmark)

Torgaard Demant, Dyveke; Lund, Karen; Finnerup, Nanna B

2015-01-01

In neuropathic pain with irritable nociceptor phenotype, up-regulation of sodium channels on nociceptors is supposed to be an important pain mechanism that may be targeted by topical sodium channel blockade. This randomised, double-blind, phenotype-panel, cross-over study with 4-week treatment pe...... had an effect on peripheral neuropathic pain, and it may be most efficacious in patients with irritable nociceptor phenotype. The lack of significant phenotype differences may be caused by too low statistical power.......In neuropathic pain with irritable nociceptor phenotype, up-regulation of sodium channels on nociceptors is supposed to be an important pain mechanism that may be targeted by topical sodium channel blockade. This randomised, double-blind, phenotype-panel, cross-over study with 4-week treatment...... periods of lidocaine 5% patch and placebo was performed to search for phenotype differences in effect. The primary efficacy measure was the total pain intensity on an 11-point numeric rating scale (NRS), and the primary objective was to compare the effect of lidocaine in patients with and without...

Variance in exposed perturbations impairs retention of visuomotor adaptation.

Science.gov (United States)

Canaveral, Cesar Augusto; Danion, Frédéric; Berrigan, Félix; Bernier, Pierre-Michel

2017-11-01

Sensorimotor control requires an accurate estimate of the state of the body. The brain optimizes state estimation by combining sensory signals with predictions of the sensory consequences of motor commands using a forward model. Given that both sensory signals and predictions are uncertain (i.e., noisy), the brain optimally weights the relative reliance on each source of information during adaptation. In support, it is known that uncertainty in the sensory predictions influences the rate and generalization of visuomotor adaptation. We investigated whether uncertainty in the sensory predictions affects the retention of a new visuomotor relationship. This was done by exposing three separate groups to a visuomotor rotation whose mean was common at 15° counterclockwise but whose variance around the mean differed (i.e., SD of 0°, 3.2°, or 4.5°). Retention was assessed by measuring the persistence of the adapted behavior in a no-vision phase. Results revealed that mean reach direction late in adaptation was similar across groups, suggesting it depended mainly on the mean of exposed rotations and was robust to differences in variance. However, retention differed across groups, with higher levels of variance being associated with a more rapid reversion toward nonadapted behavior. A control experiment ruled out the possibility that differences in retention were accounted for by differences in success rates. Exposure to variable rotations may have increased the uncertainty in sensory predictions, making the adapted forward model more labile and susceptible to change or decay. NEW & NOTEWORTHY The brain predicts the sensory consequences of motor commands through a forward model. These predictions are subject to uncertainty. We use visuomotor adaptation and modulate uncertainty in the sensory predictions by manipulating the variance in exposed rotations. Results reveal that variance does not influence the final extent of adaptation but selectively impairs the retention of

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African Journals Online (AJOL)

DR. AMINU

as the ratio of the genotypic variance to phenotypic variance. Treatments of means were compared using. DMRT, Pearson's correlation were taken to determine the types of associations between some characters and grain yield of maize. The variance of the observed values of phenotypic variance (Vp), was partitioned.

GGCX-Associated Phenotypes: An Overview in Search of Genotype-Phenotype Correlations

Directory of Open Access Journals (Sweden)

Eva Y. G. De Vilder

2017-01-01

Full Text Available Gamma-carboxylation, performed by gamma-glutamyl carboxylase (GGCX, is an enzymatic process essential for activating vitamin K-dependent proteins (VKDP with important functions in various biological processes. Mutations in the encoding GGCX gene are associated with multiple phenotypes, amongst which vitamin K-dependent coagulation factor deficiency (VKCFD1 is best known. Other patients have skin, eye, heart or bone manifestations. As genotype–phenotype correlations were never described, literature was systematically reviewed in search of patients with at least one GGCX mutation with a phenotypic description, resulting in a case series of 47 patients. Though this number was too low for statistically valid correlations—a frequent problem in orphan diseases—we demonstrate the crucial role of the horizontally transferred transmembrane domain in developing cardiac and bone manifestations. Moreover, natural history suggests ageing as the principal determinant to develop skin and eye symptoms. VKCFD1 symptoms seemed more severe in patients with both mutations in the same protein domain, though this could not be linked to a more perturbed coagulation factor function. Finally, distinct GGCX functional domains might be dedicated to carboxylation of very specific VKDP. In conclusion, this systematic review suggests that there indeed may be genotype–phenotype correlations for GGCX-related phenotypes, which can guide patient counseling and management.

Effects of Sex on Intra-Individual Variance in Urinary Solutes in Stone-Formers Collected from a Single Clinical Laboratory.

Directory of Open Access Journals (Sweden)

Guy M L Perry

Full Text Available Our work in a rodent model of urinary calcium suggests genetic and gender effects on increased residual variability in urine chemistries. Based on these findings, we hypothesized that sex would similarly be associated with residual variation in human urine solutes. Sex-related effects on residuals might affect the establishment of physiological baselines and error in medical assays.We tested the effects of sex on residual variation in urine chemistry by estimating coefficients of variation (CV for urinary solutes in paired sequential 24-h urines (≤72 hour interval in 6,758 females and 9,024 males aged 16-80 submitted to a clinical laboratory.Females had higher CVs than males for urinary phosphorus overall at the False Discovery Rate (P0.3. Males had higher CVs for citrate (P<0.01 from ages 16-45 and females higher CVs for citrate (P<0.01 from ages 56-80, suggesting effects of an extant oestral cycle on residual variance.Our findings indicate the effects of sex on residual variance of the excretion of urinary solutes including phosphorus and citrate; differences in CV by sex might reflect dietary lability, differences in the fidelity of reporting or genetic differentiation in renal solute consistency. Such an effect could complicate medical analysis by the addition of random error to phenotypic assays. Renal analysis might require explicit incorporation of heterogeneity among factorial effects, and for sex in particular.

Interoperability between phenotype and anatomy ontologies.

Science.gov (United States)

Hoehndorf, Robert; Oellrich, Anika; Rebholz-Schuhmann, Dietrich

2010-12-15

Phenotypic information is important for the analysis of the molecular mechanisms underlying disease. A formal ontological representation of phenotypic information can help to identify, interpret and infer phenotypic traits based on experimental findings. The methods that are currently used to represent data and information about phenotypes fail to make the semantics of the phenotypic trait explicit and do not interoperate with ontologies of anatomy and other domains. Therefore, valuable resources for the analysis of phenotype studies remain unconnected and inaccessible to automated analysis and reasoning. We provide a framework to formalize phenotypic descriptions and make their semantics explicit. Based on this formalization, we provide the means to integrate phenotypic descriptions with ontologies of other domains, in particular anatomy and physiology. We demonstrate how our framework leads to the capability to represent disease phenotypes, perform powerful queries that were not possible before and infer additional knowledge. http://bioonto.de/pmwiki.php/Main/PheneOntology.

Variance Reduction Techniques in Monte Carlo Methods

NARCIS (Netherlands)

Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.

2010-01-01

Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the

Decomposition of variance for spatial Cox processes

DEFF Research Database (Denmark)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models...

Decomposition of variance for spatial Cox processes

DEFF Research Database (Denmark)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

2013-01-01

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models...

Estonian total ozone climatology

Directory of Open Access Journals (Sweden)

K. Eerme

Full Text Available The climatological characteristics of total ozone over Estonia based on the Total Ozone Mapping Spectrometer (TOMS data are discussed. The mean annual cycle during 1979–2000 for the site at 58.3° N and 26.5° E is compiled. The available ground-level data interpolated before TOMS, have been used for trend detection. During the last two decades, the quasi-biennial oscillation (QBO corrected systematic decrease of total ozone from February–April was 3 ± 2.6% per decade. Before 1980, a spring decrease was not detectable. No decreasing trend was found in either the late autumn ozone minimum or in the summer total ozone. The QBO related signal in the spring total ozone has an amplitude of ± 20 DU and phase lag of 20 months. Between 1987–1992, the lagged covariance between the Singapore wind and the studied total ozone was weak. The spring (April–May and summer (June–August total ozone have the best correlation (coefficient 0.7 in the yearly cycle. The correlation between the May and August total ozone is higher than the one between the other summer months. Seasonal power spectra of the total ozone variance show preferred periods with an over 95% significance level. Since 1986, during the winter/spring, the contribution period of 32 days prevails instead of the earlier dominating 26 days. The spectral densities of the periods from 4 days to 2 weeks exhibit high interannual variability.

Key words. Atmospheric composition and structure (middle atmosphere – composition and chemistry; volcanic effects – Meteorology and atmospheric dynamics (climatology

Variance risk premia in CO_2 markets: A political perspective

International Nuclear Information System (INIS)

Reckling, Dennis

2016-01-01

The European Commission discusses the change of free allocation plans to guarantee a stable market equilibrium. Selling over-allocated contracts effectively depreciates prices and negates the effect intended by the regulator to establish a stable price mechanism for CO_2 assets. Our paper investigates mispricing and allocation issues by quantitatively analyzing variance risk premia of CO_2 markets over the course of changing regimes (Phase I-III) for three different assets (European Union Allowances, Certified Emissions Reductions and European Reduction Units). The research paper gives recommendations to regulatory bodies in order to most effectively cap the overall carbon dioxide emissions. The analysis of an enriched dataset, comprising not only of additional CO_2 assets, but also containing data from the European Energy Exchange, shows that variance risk premia are equal to a sample average of 0.69 for European Union Allowances (EUA), 0.17 for Certified Emissions Reductions (CER) and 0.81 for European Reduction Units (ERU). We identify the existence of a common risk factor across different assets that justifies the presence of risk premia. Various policy implications with regards to gaining investors’ confidence in the market are being reviewed. Consequently, we recommend the implementation of a price collar approach to support stable prices for emission allowances. - Highlights: •Enriched dataset covering all three political phases of the CO_2 markets. •Clear policy implications for regulators to most effectively cap the overall CO_2 emissions pool. •Applying a cross-asset benchmark index for variance beta estimation. •CER contracts have been analyzed with respect to variance risk premia for the first time. •Increased forecasting accuracy for CO_2 asset returns by using variance risk premia.

Phenotype- and SSR-Based Estimates of Genetic Variation between and within Two Important Elymus Species in Western and Northern China

Directory of Open Access Journals (Sweden)

Zongyu Zhang

2018-03-01

Full Text Available Elymus nutans and Elymus sibiricus are two important perennial forage grasses of the genus Elymus, widely distributed in high altitude regions of Western and Northern China, especially on the Qinghai-Tibetan Plateau. Information on phenotypic and genetic diversity is limited, but necessary for Elymus germplasm collection, conservation, and utilization. In the present study, the phenotypic and genetic differentiation of 73 accessions of the two species were evaluated using 15 phenotypic traits and 40 expressed sequence tag derived simple sequence repeat markers (EST-SSRs. The results showed that only 7.23% phenotypic differentiation (Pst existed between the two Elymus species based on fifteen quantitative traits. Principal component analysis (PCA revealed that leaf traits, spike traits, and some seed traits were dominant factors in phenotypic variation. Moreover, 396 (97.8% and 331 (87.1% polymorphic bands were generated from 40 EST-SSR primers, suggesting high levels of genetic diversity for the two species. The highest genetic diversity was found in the Northeastern Qinghai-Tibetan Plateau groups. Clustering analysis based on molecular data showed that most accessions of each Elymus species tended to group together. Similar results were described by principal coordinates analysis (PCoA and structure analysis. The molecular variance analysis (AMOVA revealed that 81.47% and 89.32% variation existed within the geographical groups for the two species, respectively. Pearson’s correlation analyses showed a strong positive correlation between Nei’s genetic diversity and annual mean temperature. These results could facilitate Elymus germplasm collection, conservation, and future breeding.

Gravity interpretation of dipping faults using the variance analysis method

International Nuclear Information System (INIS)

Essa, Khalid S

2013-01-01

A new algorithm is developed to estimate simultaneously the depth and the dip angle of a buried fault from the normalized gravity gradient data. This algorithm utilizes numerical first horizontal derivatives computed from the observed gravity anomaly, using filters of successive window lengths to estimate the depth and the dip angle of a buried dipping fault structure. For a fixed window length, the depth is estimated using a least-squares sense for each dip angle. The method is based on computing the variance of the depths determined from all horizontal gradient anomaly profiles using the least-squares method for each dip angle. The minimum variance is used as a criterion for determining the correct dip angle and depth of the buried structure. When the correct dip angle is used, the variance of the depths is always less than the variances computed using wrong dip angles. The technique can be applied not only to the true residuals, but also to the measured Bouguer gravity data. The method is applied to synthetic data with and without random errors and two field examples from Egypt and Scotland. In all cases examined, the estimated depths and other model parameters are found to be in good agreement with the actual values. (paper)

Perspective projection for variance pose face recognition from camera calibration

Science.gov (United States)

Fakhir, M. M.; Woo, W. L.; Chambers, J. A.; Dlay, S. S.

2016-04-01

Variance pose is an important research topic in face recognition. The alteration of distance parameters across variance pose face features is a challenging. We provide a solution for this problem using perspective projection for variance pose face recognition. Our method infers intrinsic camera parameters of the image which enable the projection of the image plane into 3D. After this, face box tracking and centre of eyes detection can be identified using our novel technique to verify the virtual face feature measurements. The coordinate system of the perspective projection for face tracking allows the holistic dimensions for the face to be fixed in different orientations. The training of frontal images and the rest of the poses on FERET database determine the distance from the centre of eyes to the corner of box face. The recognition system compares the gallery of images against different poses. The system initially utilises information on position of both eyes then focuses principally on closest eye in order to gather data with greater reliability. Differentiation between the distances and position of the right and left eyes is a unique feature of our work with our algorithm outperforming other state of the art algorithms thus enabling stable measurement in variance pose for each individual.

Variance-to-mean method generalized by linear difference filter technique

International Nuclear Information System (INIS)

Hashimoto, Kengo; Ohsaki, Hiroshi; Horiguchi, Tetsuo; Yamane, Yoshihiro; Shiroya, Seiji

1998-01-01

The conventional variance-to-mean method (Feynman-α method) seriously suffers the divergency of the variance under such a transient condition as a reactor power drift. Strictly speaking, then, the use of the Feynman-α is restricted to a steady state. To apply the method to more practical uses, it is desirable to overcome this kind of difficulty. For this purpose, we propose an usage of higher-order difference filter technique to reduce the effect of the reactor power drift, and derive several new formulae taking account of the filtering. The capability of the formulae proposed was demonstrated through experiments in the Kyoto University Critical Assembly. The experimental results indicate that the divergency of the variance can be effectively suppressed by the filtering technique, and that the higher-order filter becomes necessary with increasing variation rate in power

Estimation of (co)variances for genomic regions of flexible sizes

DEFF Research Database (Denmark)

Sørensen, Lars P; Janss, Luc; Madsen, Per

2012-01-01

was used. There was a clear difference in the region-wise patterns of genomic correlation among combinations of traits, with distinctive peaks indicating the presence of pleiotropic QTL. CONCLUSIONS: The results show that it is possible to estimate, genome-wide and region-wise genomic (co)variances......BACKGROUND: Multi-trait genomic models in a Bayesian context can be used to estimate genomic (co)variances, either for a complete genome or for genomic regions (e.g. per chromosome) for the purpose of multi-trait genomic selection or to gain further insight into the genomic architecture of related...... with a common prior distribution for the marker allele substitution effects and estimation of the hyperparameters in this prior distribution from the progeny means data. From the Markov chain Monte Carlo samples of the allele substitution effects, genomic (co)variances were calculated on a whole-genome level...

Subacute casemix classification for stroke rehabilitation in Australia. How well does AN-SNAP v2 explain variance in outcomes?

Science.gov (United States)

Kohler, Friedbert; Renton, Roger; Dickson, Hugh G; Estell, John; Connolly, Carol E

2011-02-01

We sought the best predictors for length of stay, discharge destination and functional improvement for inpatients undergoing rehabilitation following a stroke and compared these predictors against AN-SNAP v2. The Oxfordshire classification subgroup, sociodemographic data and functional data were collected for patients admitted between 1997 and 2007, with a diagnosis of recent stroke. The data were factor analysed using Principal Components Analysis for categorical data (CATPCA). Categorical regression analyses was performed to determine the best predictors of length of stay, discharge destination, and functional improvement. A total of 1154 patients were included in the study. Principal components analysis indicated that the data were effectively unidimensional, with length of stay being the most important component. Regression analysis demonstrated that the best predictor was the admission motor FIM score, explaining 38.9% of variance for length of stay, 37.4%.of variance for functional improvement and 16% of variance for discharge destination. The best explanatory variable in our inpatient rehabilitation service is the admission motor FIM. AN- SNAP v2 classification is a less effective explanatory variable. This needs to be taken into account when using AN-SNAP v2 classification for clinical or funding purposes.

Is residual memory variance a valid method for quantifying cognitive reserve? A longitudinal application

Science.gov (United States)

Zahodne, Laura B.; Manly, Jennifer J.; Brickman, Adam M.; Narkhede, Atul; Griffith, Erica Y.; Guzman, Vanessa A.; Schupf, Nicole; Stern, Yaakov

2016-01-01

Cognitive reserve describes the mismatch between brain integrity and cognitive performance. Older adults with high cognitive reserve are more resilient to age-related brain pathology. Traditionally, cognitive reserve is indexed indirectly via static proxy variables (e.g., years of education). More recently, cross-sectional studies have suggested that reserve can be expressed as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). The present study extends these methods to a longitudinal framework in a community-based cohort of 244 older adults who underwent two comprehensive neuropsychological and structural magnetic resonance imaging sessions over 4.6 years. On average, residual memory variance decreased over time, consistent with the idea that cognitive reserve is depleted over time. Individual differences in change in residual memory variance predicted incident dementia, independent of baseline residual memory variance. Multiple-group latent difference score models revealed tighter coupling between brain and language changes among individuals with decreasing residual memory variance. These results suggest that changes in residual memory variance may capture a dynamic aspect of cognitive reserve and could be a useful way to summarize individual cognitive responses to brain changes. Change in residual memory variance among initially non-demented older adults was a better predictor of incident dementia than residual memory variance measured at one time-point. PMID:26348002

A study of heterogeneity of environmental variance for slaughter weight in pigs

DEFF Research Database (Denmark)

Ibánez-Escriche, N; Varona, L; Sorensen, D

2008-01-01

This work presents an analysis of heterogeneity of environmental variance for slaughter weight (175 days) in pigs. This heterogeneity is associated with systematic and additive genetic effects. The model also postulates the presence of additive genetic effects affecting the mean and environmental...... variance. The study reveals the presence of genetic variation at the level of the mean and the variance, but an absence of correlation, or a small negative correlation, between both types of additive genetic effects. In addition, we show that both, the additive genetic effects on the mean and those...... on environmental variance have an important influence upon the future economic performance of selected individuals...

Biological Variance in Agricultural Products. Theoretical Considerations

NARCIS (Netherlands)

Tijskens, L.M.M.; Konopacki, P.

2003-01-01

The food that we eat is uniform neither in shape or appearance nor in internal composition or content. Since technology became increasingly important, the presence of biological variance in our food became more and more of a nuisance. Techniques and procedures (statistical, technical) were

Decomposition of variance for spatial Cox processes

DEFF Research Database (Denmark)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introducea general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive...

Regime shifts in mean-variance efficient frontiers: some international evidence

OpenAIRE

Massimo Guidolin; Federica Ria

2010-01-01

Regime switching models have been assuming a central role in financial applications because of their well-known ability to capture the presence of rich non-linear patterns in the joint distribution of asset returns. This paper examines how the presence of regimes in means, variances, and correlations of asset returns translates into explicit dynamics of the Markowitz mean-variance frontier. In particular, the paper shows both theoretically and through an application to international equity po...

Heterogeneidade dos componentes de variância na produção de leite e seus efeitos nas estimativas de herdabilidade e repetibilidade Heterogeneity of variance components in milk production and their effects on estimates of heritability and repeatability

Directory of Open Access Journals (Sweden)

Elmer Francisco Valencia Tapia

2011-06-01

Full Text Available Avaliou-se a heterogeneidade dos componentes de variância e seu efeito nas estimativas de herdabilidade e repetibilidade da produção de leite de bovinos da raça Holandesa. Os rebanhos foram agrupados de acordo com o nível de produção (baixo, médio e alto e avaliados na escala não transformada, raiz quadrada e logarítmica. Os componentes de variância foram estimados pelo método de máxima verossimilhança restrita. O modelo animal incluiu os efeitos fixos de rebanho-ano-estação e das covariáveis duração da lactação (efeito linear e idade da vaca ao parto (efeito linear e quadrático e os efeitos aleatórios genético aditivo direto, de ambiente permanente e residual. Na escala não transformada, todos os componentes de variância foram heterogêneos entre os três níveis de produção. Nesta escala, a variância residual e a fenotípica estavam associadas positivamente com o nível de produção enquanto que na escala logarítmica a associação foi negativa. A heterogeneidade da variância fenotípica e de seus componentes afetou mais as estimativas de herdabilidade que as da repetibilidade. A eficiência do processo de seleção para produção de leite poderá ser afetada pelo nível de produção em que forem estimados os parâmetros genéticos.It was evaluated the heterogeneity of components of phenotypic variance and its effects on the heritability and repeatability estimates for milk yield in Holstein cattle. The herds were grouped according to their level of production (low, medium and high and evaluated in the non-transformed, square-root and logarithmic scale. Variance components were estimated using a restricted maximum likelihood method based on an animal model that included fixed effects of herd-year-season, and as covariates the linear effect of lactation duration and the linear and quadratic effects of cow's age at calving and the random direct additive genetic, permanent environment and residual effects. In the

Methodological Considerations in Estimation of Phenotype Heritability Using Genome-Wide SNP Data, Illustrated by an Analysis of the Heritability of Height in a Large Sample of African Ancestry Adults.

Directory of Open Access Journals (Sweden)

Fang Chen

Full Text Available Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419, we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010, and estimated an additive heritability of 44.7% (se: 3.7% for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1 whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2 whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the

The pricing of long and short run variance and correlation risk in stock returns

NARCIS (Netherlands)

Cosemans, M.

2011-01-01

This paper studies the pricing of long and short run variance and correlation risk. The predictive power of the market variance risk premium for returns is driven by the correlation risk premium and the systematic part of individual variance premia. Furthermore, I find that aggregate volatility risk

A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting.

Science.gov (United States)

Ben Taieb, Souhaib; Atiya, Amir F

2016-01-01

Multistep-ahead forecasts can either be produced recursively by iterating a one-step-ahead time series model or directly by estimating a separate model for each forecast horizon. In addition, there are other strategies; some of them combine aspects of both aforementioned concepts. In this paper, we present a comprehensive investigation into the bias and variance behavior of multistep-ahead forecasting strategies. We provide a detailed review of the different multistep-ahead strategies. Subsequently, we perform a theoretical study that derives the bias and variance for a number of forecasting strategies. Finally, we conduct a Monte Carlo experimental study that compares and evaluates the bias and variance performance of the different strategies. From the theoretical and the simulation studies, we analyze the effect of different factors, such as the forecast horizon and the time series length, on the bias and variance components, and on the different multistep-ahead strategies. Several lessons are learned, and recommendations are given concerning the advantages, disadvantages, and best conditions of use of each strategy.

Joint-Attention and the Social Phenotype of School-Aged Children with ASD.

Science.gov (United States)

Mundy, Peter; Novotny, Stephanie; Swain-Lerro, Lindsey; McIntyre, Nancy; Zajic, Matt; Oswald, Tasha

2017-05-01

The validity of joint attention assessment in school-aged children with ASD is unclear (Lord, Jones, Journal of Child Psychology and Psychiatry 53(5):490-509, 2012). This study examined the feasibility and validity of a parent-report measure of joint attention related behaviors in verbal children and adolescents with ASD. Fifty-two children with ASD and 34 controls were assessed with the Childhood Joint Attention Rating Scale (C-JARS). The C-JARS exhibited internally consistency, α = 0.88, and one factor explained 49% of the scale variance. Factor scores correctly identified between 88 and 94% of the children with ASD and 62-82% of controls. These scores were correlated with the ADOS-2, but not other parent-report symptom measures. The C-JARS appears to assess a unique dimension of the social-phenotype of children with ASD.

Variance inflation in high dimensional Support Vector Machines

DEFF Research Database (Denmark)

Abrahamsen, Trine Julie; Hansen, Lars Kai

2013-01-01

Many important machine learning models, supervised and unsupervised, are based on simple Euclidean distance or orthogonal projection in a high dimensional feature space. When estimating such models from small training sets we face the problem that the span of the training data set input vectors...... the case of Support Vector Machines (SVMS) and we propose a non-parametric scheme to restore proper generalizability. We illustrate the algorithm and its ability to restore performance on a wide range of benchmark data sets....... follow a different probability law with less variance. While the problem and basic means to reconstruct and deflate are well understood in unsupervised learning, the case of supervised learning is less well understood. We here investigate the effect of variance inflation in supervised learning including...

Sex hormone binding globulin phenotypes

DEFF Research Database (Denmark)

Cornelisse, M M; Bennett, Patrick; Christiansen, M

1994-01-01

Human sex hormone binding globulin (SHBG) is encoded by a normal and a variant allele. The resulting SHBG phenotypes (the homozygous normal SHBG, the heterozygous SHBG and the homozygous variant SHBG phenotype) can be distinguished by their electrophoretic patterns. We developed a novel detection....... This method of detection was used to determine the distribution of SHBG phenotypes in healthy controls of both sexes and in five different pathological conditions characterized by changes in the SHBG level or endocrine disturbances (malignant and benign ovarian neoplasms, hirsutism, liver cirrhosis...... on the experimental values. Differences in SHBG phenotypes do not appear to have any clinical significance and no sex difference was found in the SHBG phenotype distribution....

Feynman variance-to-mean in the context of passive neutron coincidence counting

Energy Technology Data Exchange (ETDEWEB)

Croft, S., E-mail: scroft@lanl.gov [Los Alamos National Laboratory, PO Box 1663, Los Alamos, NM 87545 (United States); Favalli, A.; Hauck, D.K.; Henzlova, D.; Santi, P.A. [Los Alamos National Laboratory, PO Box 1663, Los Alamos, NM 87545 (United States)

2012-09-11

Passive Neutron Coincidence Counting (PNCC) based on shift register autocorrelation time analysis of the detected neutron pulse train is an important Nondestructive Assay (NDA) method. It is used extensively in the quantification of plutonium and other spontaneously fissile materials for purposes of nuclear materials accountancy. In addition to the totals count rate, which is also referred to as the singles, gross or trigger rate, a quantity known as the reals coincidence rate, also called the pairs or doubles, is obtained from the difference between the measured neutron multiplicities in two measurement gates triggered by the incoming events on the pulse train. The reals rate is a measure of the number of time correlated pairs present on the pulse train and this can be related to the fission rates (and hence material mass) since fissions emit neutrons in bursts which are also detected in characteristic clusters. A closely related measurement objective is the determination of the reactivity of systems as they approach criticality. In this field an alternative autocorrelation signature is popular, the so called Feynman variance-to-mean technique which makes use of the multiplicity histogram formed the periodic, or clock-triggered opening of a coincidence gate. Workers in these two application areas share common challenges and improvement opportunities but are often separated by tradition, problem focus and technical language. The purpose of this paper is to recognize the close link between the Feynman variance-to-mean metric and traditional PNCC using shift register logic applied to correlated pulse trains. We, show using relationships for the late-gate (or accidentals) histogram recorded using a multiplicity shift register, how the Feynman Y-statistic, defined as the excess variance-to-mean ratio, can be expressed in terms of the singles and doubles rates familiar to the safeguards and waste assay communities. These two specialisms now have a direct bridge between

Studying Variance in the Galactic Ultra-compact Binary Population

Science.gov (United States)

Larson, Shane; Breivik, Katelyn

2017-01-01

In the years preceding LISA, Milky Way compact binary population simulations can be used to inform the science capabilities of the mission. Galactic population simulation efforts generally focus on high fidelity models that require extensive computational power to produce a single simulated population for each model. Each simulated population represents an incomplete sample of the functions governing compact binary evolution, thus introducing variance from one simulation to another. We present a rapid Monte Carlo population simulation technique that can simulate thousands of populations on week-long timescales, thus allowing a full exploration of the variance associated with a binary stellar evolution model.

Genotype and Phenotype of 101 Dutch Patients with Congenital Stationary Night Blindness

NARCIS (Netherlands)

Bijveld, M.M.C.; Florijn, R.J.; Bergen, A.A.B.; van den Born, L.I.; Kamermans, M.; Prick, L.; Riemslag, F.C.C.; van Schooneveld, M.J.; Kappers, A.M.L.; van Genderen, M.M.

2013-01-01

Objective: To investigate the relative frequency of the genetic causes of the Schubert-Bornschein type of congenital stationary night blindness (CSNB) and to determine the genotype-phenotype correlations in CSNB1 and CSNB2. Design: Clinic-based, longitudinal, multicenter study. Participants: A total

Text-based phenotypic profiles incorporating biochemical phenotypes of inborn errors of metabolism improve phenomics-based diagnosis.

Science.gov (United States)

Lee, Jessica J Y; Gottlieb, Michael M; Lever, Jake; Jones, Steven J M; Blau, Nenad; van Karnebeek, Clara D M; Wasserman, Wyeth W

2018-05-01

Phenomics is the comprehensive study of phenotypes at every level of biology: from metabolites to organisms. With high throughput technologies increasing the scope of biological discoveries, the field of phenomics has been developing rapid and precise methods to collect, catalog, and analyze phenotypes. Such methods have allowed phenotypic data to be widely used in medical applications, from assisting clinical diagnoses to prioritizing genomic diagnoses. To channel the benefits of phenomics into the field of inborn errors of metabolism (IEM), we have recently launched IEMbase, an expert-curated knowledgebase of IEM and their disease-characterizing phenotypes. While our efforts with IEMbase have realized benefits, taking full advantage of phenomics requires a comprehensive curation of IEM phenotypes in core phenomics projects, which is dependent upon contributions from the IEM clinical and research community. Here, we assess the inclusion of IEM biochemical phenotypes in a core phenomics project, the Human Phenotype Ontology. We then demonstrate the utility of biochemical phenotypes using a text-based phenomics method to predict gene-disease relationships, showing that the prediction of IEM genes is significantly better using biochemical rather than clinical profiles. The findings herein provide a motivating goal for the IEM community to expand the computationally accessible descriptions of biochemical phenotypes associated with IEM in phenomics resources.

Variance estimates for transport in stochastic media by means of the master equation

International Nuclear Information System (INIS)

Pautz, S. D.; Franke, B. C.; Prinja, A. K.

2013-01-01

The master equation has been used to examine properties of transport in stochastic media. It has been shown previously that not only may the Levermore-Pomraning (LP) model be derived from the master equation for a description of ensemble-averaged transport quantities, but also that equations describing higher-order statistical moments may be obtained. We examine in greater detail the equations governing the second moments of the distribution of the angular fluxes, from which variances may be computed. We introduce a simple closure for these equations, as well as several models for estimating the variances of derived transport quantities. We revisit previous benchmarks for transport in stochastic media in order to examine the error of these new variance models. We find, not surprisingly, that the errors in these variance estimates are at least as large as the corresponding estimates of the average, and sometimes much larger. We also identify patterns in these variance estimates that may help guide the construction of more accurate models. (authors)

Markov switching mean-variance frontier dynamics: theory and international evidence

OpenAIRE

M. Guidolin; F. Ria

2010-01-01

It is well-known that regime switching models are able to capture the presence of rich non-linear patterns in the joint distribution of asset returns. After reviewing key concepts and technical issues related to specifying, estimating, and using multivariate Markov switching models in financial applications, in this paper we map the presence of regimes in means, variances, and covariances of asset returns into explicit dynamics of the Markowitz mean-variance frontier. In particular, we show b...

Visual SLAM Using Variance Grid Maps

Science.gov (United States)

Howard, Andrew B.; Marks, Tim K.

2011-01-01

An algorithm denoted Gamma-SLAM performs further processing, in real time, of preprocessed digitized images acquired by a stereoscopic pair of electronic cameras aboard an off-road robotic ground vehicle to build accurate maps of the terrain and determine the location of the vehicle with respect to the maps. Part of the name of the algorithm reflects the fact that the process of building the maps and determining the location with respect to them is denoted simultaneous localization and mapping (SLAM). Most prior real-time SLAM algorithms have been limited in applicability to (1) systems equipped with scanning laser range finders as the primary sensors in (2) indoor environments (or relatively simply structured outdoor environments). The few prior vision-based SLAM algorithms have been feature-based and not suitable for real-time applications and, hence, not suitable for autonomous navigation on irregularly structured terrain. The Gamma-SLAM algorithm incorporates two key innovations: Visual odometry (in contradistinction to wheel odometry) is used to estimate the motion of the vehicle. An elevation variance map (in contradistinction to an occupancy or an elevation map) is used to represent the terrain. The Gamma-SLAM algorithm makes use of a Rao-Blackwellized particle filter (RBPF) from Bayesian estimation theory for maintaining a distribution over poses and maps. The core idea of the RBPF approach is that the SLAM problem can be factored into two parts: (1) finding the distribution over robot trajectories, and (2) finding the map conditioned on any given trajectory. The factorization involves the use of a particle filter in which each particle encodes both a possible trajectory and a map conditioned on that trajectory. The base estimate of the trajectory is derived from visual odometry, and the map conditioned on that trajectory is a Cartesian grid of elevation variances. In comparison with traditional occupancy or elevation grid maps, the grid elevation variance

Temporal variance reverses the impact of high mean intensity of stress in climate change experiments.

Science.gov (United States)

Benedetti-Cecchi, Lisandro; Bertocci, Iacopo; Vaselli, Stefano; Maggi, Elena

2006-10-01

Extreme climate events produce simultaneous changes to the mean and to the variance of climatic variables over ecological time scales. While several studies have investigated how ecological systems respond to changes in mean values of climate variables, the combined effects of mean and variance are poorly understood. We examined the response of low-shore assemblages of algae and invertebrates of rocky seashores in the northwest Mediterranean to factorial manipulations of mean intensity and temporal variance of aerial exposure, a type of disturbance whose intensity and temporal patterning of occurrence are predicted to change with changing climate conditions. Effects of variance were often in the opposite direction of those elicited by changes in the mean. Increasing aerial exposure at regular intervals had negative effects both on diversity of assemblages and on percent cover of filamentous and coarsely branched algae, but greater temporal variance drastically reduced these effects. The opposite was observed for the abundance of barnacles and encrusting coralline algae, where high temporal variance of aerial exposure either reversed a positive effect of mean intensity (barnacles) or caused a negative effect that did not occur under low temporal variance (encrusting algae). These results provide the first experimental evidence that changes in mean intensity and temporal variance of climatic variables affect natural assemblages of species interactively, suggesting that high temporal variance may mitigate the ecological impacts of ongoing and predicted climate changes.

Genetic and environmental variance in content dimensions of the MMPI.

Science.gov (United States)

Rose, R J

1988-08-01

To evaluate genetic and environmental variance in the Minnesota Multiphasic Personality Inventory (MMPI), I studied nine factor scales identified in the first item factor analysis of normal adult MMPIs in a sample of 820 adolescent and young adult co-twins. Conventional twin comparisons documented heritable variance in six of the nine MMPI factors (Neuroticism, Psychoticism, Extraversion, Somatic Complaints, Inadequacy, and Cynicism), whereas significant influence from shared environmental experience was found for four factors (Masculinity versus Femininity, Extraversion, Religious Orthodoxy, and Intellectual Interests). Genetic variance in the nine factors was more evident in results from twin sisters than those of twin brothers, and a developmental-genetic analysis, using hierarchical multiple regressions of double-entry matrixes of the twins' raw data, revealed that in four MMPI factor scales, genetic effects were significantly modulated by age or gender or their interaction during the developmental period from early adolescence to early adulthood.

Is residual memory variance a valid method for quantifying cognitive reserve? A longitudinal application.

Science.gov (United States)

Zahodne, Laura B; Manly, Jennifer J; Brickman, Adam M; Narkhede, Atul; Griffith, Erica Y; Guzman, Vanessa A; Schupf, Nicole; Stern, Yaakov

2015-10-01

Cognitive reserve describes the mismatch between brain integrity and cognitive performance. Older adults with high cognitive reserve are more resilient to age-related brain pathology. Traditionally, cognitive reserve is indexed indirectly via static proxy variables (e.g., years of education). More recently, cross-sectional studies have suggested that reserve can be expressed as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). The present study extends these methods to a longitudinal framework in a community-based cohort of 244 older adults who underwent two comprehensive neuropsychological and structural magnetic resonance imaging sessions over 4.6 years. On average, residual memory variance decreased over time, consistent with the idea that cognitive reserve is depleted over time. Individual differences in change in residual memory variance predicted incident dementia, independent of baseline residual memory variance. Multiple-group latent difference score models revealed tighter coupling between brain and language changes among individuals with decreasing residual memory variance. These results suggest that changes in residual memory variance may capture a dynamic aspect of cognitive reserve and could be a useful way to summarize individual cognitive responses to brain changes. Change in residual memory variance among initially non-demented older adults was a better predictor of incident dementia than residual memory variance measured at one time-point. Copyright © 2015. Published by Elsevier Ltd.

Heritability, variance components and genetic advance of some ...

African Journals Online (AJOL)

Heritability, variance components and genetic advance of some yield and yield related traits in Ethiopian ... African Journal of Biotechnology ... randomized complete block design at Adet Agricultural Research Station in 2008 cropping season.

Genotype-Phenotype Study of the Middle Gangetic Plain in India Shows Association of rs2470102 with Skin Pigmentation.

Science.gov (United States)

Mishra, Anshuman; Nizammuddin, Sheikh; Mallick, Chandana Basu; Singh, Sakshi; Prakash, Satya; Siddiqui, Niyamat Ali; Rai, Niraj; Carlus, S Justin; Sudhakar, Digumarthi V S; Tripathi, Vishnu P; Möls, Märt; Kim-Howard, Xana; Dewangan, Hemlata; Mishra, Abhishek; Reddy, Alla G; Roy, Biswajit; Pandey, Krishna; Chaubey, Gyaneshwer; Das, Pradeep; Nath, Swapan K; Singh, Lalji; Thangaraj, Kumarasamy

2017-03-01

Our understanding of the genetics of skin pigmentation has been largely skewed towards populations of European ancestry, imparting less attention to South Asian populations, who behold huge pigmentation diversity. Here, we investigate skin pigmentation variation in a cohort of 1,167 individuals in the Middle Gangetic Plain of the Indian subcontinent. Our data confirm the association of rs1426654 with skin pigmentation among South Asians, consistent with previous studies, and also show association for rs2470102 single nucleotide polymorphism. Our haplotype analyses further help us delineate the haplotype distribution across social categories and skin color. Taken together, our findings suggest that the social structure defined by the caste system in India has a profound influence on the skin pigmentation patterns of the subcontinent. In particular, social category and associated single nucleotide polymorphisms explain about 32% and 6.4%, respectively, of the total phenotypic variance. Phylogeography of the associated single nucleotide polymorphisms studied across 52 diverse populations of the Indian subcontinent shows wide presence of the derived alleles, although their frequencies vary across populations. Our results show that both polymorphisms (rs1426654 and rs2470102) play an important role in the skin pigmentation diversity of South Asians. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Childhood asthma-predictive phenotype.

Science.gov (United States)

Guilbert, Theresa W; Mauger, David T; Lemanske, Robert F

2014-01-01

Wheezing is a fairly common symptom in early childhood, but only some of these toddlers will experience continued wheezing symptoms in later childhood. The definition of the asthma-predictive phenotype is in children with frequent, recurrent wheezing in early life who have risk factors associated with the continuation of asthma symptoms in later life. Several asthma-predictive phenotypes were developed retrospectively based on large, longitudinal cohort studies; however, it can be difficult to differentiate these phenotypes clinically as the expression of symptoms, and risk factors can change with time. Genetic, environmental, developmental, and host factors and their interactions may contribute to the development, severity, and persistence of the asthma phenotype over time. Key characteristics that distinguish the childhood asthma-predictive phenotype include the following: male sex; a history of wheezing, with lower respiratory tract infections; history of parental asthma; history of atopic dermatitis; eosinophilia; early sensitization to food or aeroallergens; or lower lung function in early life. Copyright © 2014 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Quantum mechanics as total physical theory

International Nuclear Information System (INIS)

Slavnov, D.A.

2002-01-01

It is shown that the principles of the total physical theory and conclusions of the standard quantum mechanics are not at such an antagonistic variance as it is usually accepted. The axioms, which make it possible to plot the renewed mathematical scheme of the quantum mechanics are formulated within the frames of the algebraic approach. The above scheme includes the standard mathematical apparatus of the quantum mechanics. Simultaneously there exists the mathematical object, which adequately describes the individual experiment. The examples of applying the proposed scheme is presented [ru

Modality-Driven Classification and Visualization of Ensemble Variance

Energy Technology Data Exchange (ETDEWEB)

Bensema, Kevin; Gosink, Luke; Obermaier, Harald; Joy, Kenneth I.

2016-10-01

Advances in computational power now enable domain scientists to address conceptual and parametric uncertainty by running simulations multiple times in order to sufficiently sample the uncertain input space. While this approach helps address conceptual and parametric uncertainties, the ensemble datasets produced by this technique present a special challenge to visualization researchers as the ensemble dataset records a distribution of possible values for each location in the domain. Contemporary visualization approaches that rely solely on summary statistics (e.g., mean and variance) cannot convey the detailed information encoded in ensemble distributions that are paramount to ensemble analysis; summary statistics provide no information about modality classification and modality persistence. To address this problem, we propose a novel technique that classifies high-variance locations based on the modality of the distribution of ensemble predictions. Additionally, we develop a set of confidence metrics to inform the end-user of the quality of fit between the distribution at a given location and its assigned class. We apply a similar method to time-varying ensembles to illustrate the relationship between peak variance and bimodal or multimodal behavior. These classification schemes enable a deeper understanding of the behavior of the ensemble members by distinguishing between distributions that can be described by a single tendency and distributions which reflect divergent trends in the ensemble.

Estimation of genetic parameters and their sampling variances for quantitative traits in the type 2 modified augmented design

OpenAIRE

Frank M. You; Qijian Song; Gaofeng Jia; Yanzhao Cheng; Scott Duguid; Helen Booker; Sylvie Cloutier

2016-01-01

The type 2 modified augmented design (MAD2) is an efficient unreplicated experimental design used for evaluating large numbers of lines in plant breeding and for assessing genetic variation in a population. Statistical methods and data adjustment for soil heterogeneity have been previously described for this design. In the absence of replicated test genotypes in MAD2, their total variance cannot be partitioned into genetic and error components as required to estimate heritability and genetic ...

Active smoking and COPD phenotype: distribution and impact on prognostic factors

Directory of Open Access Journals (Sweden)

Riesco JA

2017-07-01

Full Text Available Juan Antonio Riesco,1,2 Bernardino Alcázar,3 Juan Antonio Trigueros,4 Anna Campuzano,5 Joselín Pérez,5 José Luis Lorenzo5 1Pulmonology Department, Hospital San Pedro de Alcántara, 2Centro de Investigación en Red de Enfermedades Respiratorias (CIBERES, Cáceres, 3Pulmonology Department, Hospital La Loja, Granada, 4Centro de Salud de Menasalvas, Toledo, 5Grupo Ferrer Internacional, Barcelona, Spain Purpose: Smoking can affect both the phenotypic expression of COPD and factors such as disease severity, quality of life, and comorbidities. Our objective was to evaluate if the impact of active smoking on these factors varies according to the disease phenotype. Patients and methods: This was a Spanish, observational, cross-sectional, multicenter study of patients with a diagnosis of COPD. Smoking rates were described among four different phenotypes (non-exacerbators, asthma-COPD overlap syndrome [ACOS], exacerbators with emphysema, and exacerbators with chronic bronchitis, and correlated with disease severity (body mass index, obstruction, dyspnea and exacerbations [BODEx] index and dyspnea grade, quality of life according to the COPD assessment test (CAT, and presence of comorbidities, according to phenotypic expression. Results: In total, 1,610 patients were recruited, of whom 46.70% were classified as non-exacerbators, 14.53% as ACOS, 16.37% as exacerbators with emphysema, and 22.40% as exacerbators with chronic bronchitis. Smokers were predominant in the latter 2 groups (58.91% and 57.67%, respectively, P=0.03. Active smoking was significantly associated with better quality of life and a higher dyspnea grade, although differences were observed depending on clinical phenotype. Conclusion: Active smoking is more common among exacerbator phenotypes and appears to affect quality of life and dyspnea grade differently, depending on the clinical expression of the disease. Keywords: COPD, phenotype, smoking, prognostic factors, quality of life 

The variance of the locally measured Hubble parameter explained with different estimators

DEFF Research Database (Denmark)

Odderskov, Io Sandberg Hess; Hannestad, Steen; Brandbyge, Jacob

2017-01-01

We study the expected variance of measurements of the Hubble constant, H0, as calculated in either linear perturbation theory or using non-linear velocity power spectra derived from N-body simulations. We compare the variance with that obtained by carrying out mock observations in the N......-body simulations, and show that the estimator typically used for the local Hubble constant in studies based on perturbation theory is different from the one used in studies based on N-body simulations. The latter gives larger weight to distant sources, which explains why studies based on N-body simulations tend...... to obtain a smaller variance than that found from studies based on the power spectrum. Although both approaches result in a variance too small to explain the discrepancy between the value of H0 from CMB measurements and the value measured in the local universe, these considerations are important in light...

Variance Risk Premia on Stocks and Bonds

DEFF Research Database (Denmark)

Mueller, Philippe; Sabtchevsky, Petar; Vedolin, Andrea

Investors in fixed income markets are willing to pay a very large premium to be hedged against shocks in expected volatility and the size of this premium can be studied through variance swaps. Using thirty years of option and high-frequency data, we document the following novel stylized facts...

A “Forward Genomics” Approach Links Genotype to Phenotype using Independent Phenotypic Losses among Related Species

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Michael Hiller

2012-10-01

Full Text Available Genotype-phenotype mapping is hampered by countless genomic changes between species. We introduce a computational “forward genomics” strategy that—given only an independently lost phenotype and whole genomes—matches genomic and phenotypic loss patterns to associate specific genomic regions with this phenotype. We conducted genome-wide screens for two metabolic phenotypes. First, our approach correctly matches the inactivated Gulo gene exactly with the species that lost the ability to synthesize vitamin C. Second, we attribute naturally low biliary phospholipid levels in guinea pigs and horses to the inactivated phospholipid transporter Abcb4. Human ABCB4 mutations also result in low phospholipid levels but lead to severe liver disease, suggesting compensatory mechanisms in guinea pig and horse. Our simulation studies, counts of independent changes in existing phenotype surveys, and the forthcoming availability of many new genomes all suggest that forward genomics can be applied to many phenotypes, including those relevant for human evolution and disease.

Influência da heterogeneidade de variâncias na avaliação genética de bovinos de corte da raça Tabapuã Influence of heterogeneity of variances on genetic evaluation of Tabapuã beef cattle

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J.E.G. Campelo

2003-12-01

Full Text Available Verificou-se a influência da heterogeneidade de variâncias na avaliação genética de bovinos de corte da raça Tabapuã. Dados de pesos corrigidos aos 120, 240 e 420 dias de idade foram estratificados com base no desvio-padrão fenotípico do peso aos 120 dias dos grupos de contemporâneos em três classes: baixo (18,9kg desvio-padrão. Nas análises de múltiplas características, em que o peso foi considerado característica distinta em cada classe de desvio-padrão, constatou-se que as variâncias genéticas e residuais foram maiores com o aumento do desvio-padrão da classe. As herdabilidades foram 0,26, 0,32 e 0,37 (peso aos 120 dias, 0,28, 0,35 e 0,35 (peso aos 240 dias e 0,14, 0,18 e 0,18 (peso aos 420 dias nas classes de baixo, médio e alto desvio-padrão, respectivamente. As correlações genéticas entre o mesmo peso, nas classes de baixo e alto desvio-padrão foram inferiores a 0,80. As correlações entre os valores genéticos, obtidos de análises múltiplas e de análise geral (sem as classes, foram superiores a 0,93. Observou-se que os reprodutores seriam classificados de forma similar se for considerada ou não a presença de variâncias heterogêneas nas análises.Data from Tabapuã beef cattle were used to study the influence of variance heterogeneity on genetic evaluation. Adjusted weights at 120, 240 and 420 days of age were classified in three classes of standard deviation: low (18.9kg, based on phenotypic standard deviation of the weight at 120 days of age of the contemporary groups. Multiple trait analyses, considering each class of phenotypic standard deviation as a distinct trait, were performed. The genetic and residual variances increased as the phenotypic standard deviation of the class increased. Heritabilities for low, medium and high phenotypic standard deviation classes were 0.26, 0.32 and 0.37 (weight at 120 days, 0.28, 0.35 and 0.35 (weight at 240 days and 0.14, 0.18 and 0.18 (weight at 420 days

Genetic and environmental dissections of sub-phenotypes of metabolic syndrome in the chinese population: a twin-based heritability study

DEFF Research Database (Denmark)

Duan, Haiping; Pang, Zengchang; Zhang, Dongfeng

2011-01-01

contains 654 twins collected in the Qingdao municipality. A total of 10 phenotypes covering anthropometric measurements, plasma glucose levels, lipids, blood pressures etc. were examined. Univariate and bivariate structural equation models were fitted for assessing the genetic and environmental...... contributions. Results: The AE model combining additive genetic (A) and unique environmental (E) factors produced the best fit for all phenotypes except for triglyceride. Modest to high heritability estimates were obtained in univariate analysis ranging from 0.5 for total cholesterol to 0.78 for weight...

On Mean-Variance Hedging of Bond Options with Stochastic Risk Premium Factor

NARCIS (Netherlands)

Aihara, ShinIchi; Bagchi, Arunabha; Kumar, Suresh K.

2014-01-01

We consider the mean-variance hedging problem for pricing bond options using the yield curve as the observation. The model considered contains infinite-dimensional noise sources with the stochastically- varying risk premium. Hence our model is incomplete. We consider mean-variance hedging under the

Clinical phenotype-based gene prioritization: an initial study using semantic similarity and the human phenotype ontology.

Science.gov (United States)

Masino, Aaron J; Dechene, Elizabeth T; Dulik, Matthew C; Wilkens, Alisha; Spinner, Nancy B; Krantz, Ian D; Pennington, Jeffrey W; Robinson, Peter N; White, Peter S

2014-07-21

Exome sequencing is a promising method for diagnosing patients with a complex phenotype. However, variant interpretation relative to patient phenotype can be challenging in some scenarios, particularly clinical assessment of rare complex phenotypes. Each patient's sequence reveals many possibly damaging variants that must be individually assessed to establish clear association with patient phenotype. To assist interpretation, we implemented an algorithm that ranks a given set of genes relative to patient phenotype. The algorithm orders genes by the semantic similarity computed between phenotypic descriptors associated with each gene and those describing the patient. Phenotypic descriptor terms are taken from the Human Phenotype Ontology (HPO) and semantic similarity is derived from each term's information content. Model validation was performed via simulation and with clinical data. We simulated 33 Mendelian diseases with 100 patients per disease. We modeled clinical conditions by adding noise and imprecision, i.e. phenotypic terms unrelated to the disease and terms less specific than the actual disease terms. We ranked the causative gene against all 2488 HPO annotated genes. The median causative gene rank was 1 for the optimal and noise cases, 12 for the imprecision case, and 60 for the imprecision with noise case. Additionally, we examined a clinical cohort of subjects with hearing impairment. The disease gene median rank was 22. However, when also considering the patient's exome data and filtering non-exomic and common variants, the median rank improved to 3. Semantic similarity can rank a causative gene highly within a gene list relative to patient phenotype characteristics, provided that imprecision is mitigated. The clinical case results suggest that phenotype rank combined with variant analysis provides significant improvement over the individual approaches. We expect that this combined prioritization approach may increase accuracy and decrease effort for

The Autism-Spectrum Quotient--Italian version: a cross-cultural confirmation of the broader autism phenotype.

Science.gov (United States)

Ruta, Liliana; Mazzone, Domenico; Mazzone, Luigi; Wheelwright, Sally; Baron-Cohen, Simon

2012-04-01

The Autism Spectrum Quotient (AQ) has been used to define the 'broader' (BAP), 'medium' (MAP) and 'narrow' autism phenotypes (NAP). We used a new Italian version of the AQ to test if difference on AQ scores and the distribution of BAP, MAP and NAP in autism parents (n = 245) versus control parents (n = 300) were replicated in a Sicilian sample. Parents of children with autism spectrum conditions scored higher than the control parents on total AQ, social skills and communication subscales, and exhibited higher rates of BAP, MAP and NAP. We conclude that the Italian AQ is a cross-culturally reliable measure of these different phenotypes, and can be used to identify a phenotypic gradient of severity of autistic traits in families. To understand the molecular basis of these phenotypes will require its use in genetic association studies.

Problems of variance reduction in the simulation of random variables

International Nuclear Information System (INIS)

Lessi, O.

1987-01-01

The definition of the uniform linear generator is given and some of the mostly used tests to evaluate the uniformity and the independence of the obtained determinations are listed. The problem of calculating, through simulation, some moment W of a random variable function is taken into account. The Monte Carlo method enables the moment W to be estimated and the estimator variance to be obtained. Some techniques for the construction of other estimators of W with a reduced variance are introduced

Mean-variance portfolio allocation with a value at risk constraint

OpenAIRE

Enrique Sentana

2001-01-01

In this Paper, I first provide a simple unifying approach to static Mean-Variance analysis and Value at Risk, which highlights their similarities and differences. Then I use it to explain how fund managers can take investment decisions that satisfy the VaR restrictions imposed on them by regulators, within the well-known Mean-Variance allocation framework. I do so by introducing a new type of line to the usual mean-standard deviation diagram, called IsoVaR,which represents all the portfolios ...

Variance-based sensitivity analysis for wastewater treatment plant modelling.

Science.gov (United States)

Cosenza, Alida; Mannina, Giorgio; Vanrolleghem, Peter A; Neumann, Marc B

2014-02-01

Global sensitivity analysis (GSA) is a valuable tool to support the use of mathematical models that characterise technical or natural systems. In the field of wastewater modelling, most of the recent applications of GSA use either regression-based methods, which require close to linear relationships between the model outputs and model factors, or screening methods, which only yield qualitative results. However, due to the characteristics of membrane bioreactors (MBR) (non-linear kinetics, complexity, etc.) there is an interest to adequately quantify the effects of non-linearity and interactions. This can be achieved with variance-based sensitivity analysis methods. In this paper, the Extended Fourier Amplitude Sensitivity Testing (Extended-FAST) method is applied to an integrated activated sludge model (ASM2d) for an MBR system including microbial product formation and physical separation processes. Twenty-one model outputs located throughout the different sections of the bioreactor and 79 model factors are considered. Significant interactions among the model factors are found. Contrary to previous GSA studies for ASM models, we find the relationship between variables and factors to be non-linear and non-additive. By analysing the pattern of the variance decomposition along the plant, the model factors having the highest variance contributions were identified. This study demonstrates the usefulness of variance-based methods in membrane bioreactor modelling where, due to the presence of membranes and different operating conditions than those typically found in conventional activated sludge systems, several highly non-linear effects are present. Further, the obtained results highlight the relevant role played by the modelling approach for MBR taking into account simultaneously biological and physical processes. © 2013.

Fundamentals of exploratory analysis of variance

CERN Document Server

Hoaglin, David C; Tukey, John W

2009-01-01

The analysis of variance is presented as an exploratory component of data analysis, while retaining the customary least squares fitting methods. Balanced data layouts are used to reveal key ideas and techniques for exploration. The approach emphasizes both the individual observations and the separate parts that the analysis produces. Most chapters include exercises and the appendices give selected percentage points of the Gaussian, t, F chi-squared and studentized range distributions.

On the Likely Utility of Hybrid Weights Optimized for Variances in Hybrid Error Covariance Models

Science.gov (United States)

Satterfield, E.; Hodyss, D.; Kuhl, D.; Bishop, C. H.

2017-12-01

Because of imperfections in ensemble data assimilation schemes, one cannot assume that the ensemble covariance is equal to the true error covariance of a forecast. Previous work demonstrated how information about the distribution of true error variances given an ensemble sample variance can be revealed from an archive of (observation-minus-forecast, ensemble-variance) data pairs. Here, we derive a simple and intuitively compelling formula to obtain the mean of this distribution of true error variances given an ensemble sample variance from (observation-minus-forecast, ensemble-variance) data pairs produced by a single run of a data assimilation system. This formula takes the form of a Hybrid weighted average of the climatological forecast error variance and the ensemble sample variance. Here, we test the extent to which these readily obtainable weights can be used to rapidly optimize the covariance weights used in Hybrid data assimilation systems that employ weighted averages of static covariance models and flow-dependent ensemble based covariance models. Univariate data assimilation and multi-variate cycling ensemble data assimilation are considered. In both cases, it is found that our computationally efficient formula gives Hybrid weights that closely approximate the optimal weights found through the simple but computationally expensive process of testing every plausible combination of weights.

A new variance stabilizing transformation for gene expression data analysis.

Science.gov (United States)

Kelmansky, Diana M; Martínez, Elena J; Leiva, Víctor

2013-12-01

In this paper, we introduce a new family of power transformations, which has the generalized logarithm as one of its members, in the same manner as the usual logarithm belongs to the family of Box-Cox power transformations. Although the new family has been developed for analyzing gene expression data, it allows a wider scope of mean-variance related data to be reached. We study the analytical properties of the new family of transformations, as well as the mean-variance relationships that are stabilized by using its members. We propose a methodology based on this new family, which includes a simple strategy for selecting the family member adequate for a data set. We evaluate the finite sample behavior of different classical and robust estimators based on this strategy by Monte Carlo simulations. We analyze real genomic data by using the proposed transformation to empirically show how the new methodology allows the variance of these data to be stabilized.

Pricing perpetual American options under multiscale stochastic elasticity of variance

International Nuclear Information System (INIS)

Yoon, Ji-Hun

2015-01-01

Highlights: • We study the effects of the stochastic elasticity of variance on perpetual American option. • Our SEV model consists of a fast mean-reverting factor and a slow mean-revering factor. • A slow scale factor has a very significant impact on the option price. • We analyze option price structures through the market prices of elasticity risk. - Abstract: This paper studies pricing the perpetual American options under a constant elasticity of variance type of underlying asset price model where the constant elasticity is replaced by a fast mean-reverting Ornstein–Ulenbeck process and a slowly varying diffusion process. By using a multiscale asymptotic analysis, we find the impact of the stochastic elasticity of variance on the option prices and the optimal exercise prices with respect to model parameters. Our results enhance the existing option price structures in view of flexibility and applicability through the market prices of elasticity risk

Phenotypic stability and genetic gains in six-year girth growth of Hevea clones

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Paulo de Souza Gonçalves

1999-07-01

Full Text Available Rubber tree [Hevea brasiliensis (Willd. ex Adr. de Juss. Müell. Arg.] budgrafts of seven clones were evaluated on five contrasting sites in the plateau region of the São Paulo State, Brazil. The objective of this work was to study the phenotypic stability for girth growth. The experimental design was a randomized block design with three replications and seven treatments. Analysis of variance of girth at six-year plant growth indicated a highly significant clone x site interaction. Only linear sites and clone x site components of clone x year interaction were significant, indicating that the performance of clones over sites for this trait could be predicted. The clones GT 1 and PB 235 showed the greatest stability in relation to girth growth, with foreseen responses to change, introduced in the sites. The clones PB 235 and IAN 873 showed significative difference in relation to regression coefficient, representing clones with specific adaptability on favorable and unfavorable sites respectively. The clone GT 1 became the most promissory one in the study of stability and adaptability even showing low girth growth. Expected genetic gains from planting sites, along with estimates of clonal variance and repeatability of clonal means are generally greatest or close to the greatest when selection is done at the same site.

Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

International Nuclear Information System (INIS)

Yu, Zhiyong

2013-01-01

This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right

Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

Energy Technology Data Exchange (ETDEWEB)

Yu, Zhiyong, E-mail: yuzhiyong@sdu.edu.cn [Shandong University, School of Mathematics (China)

2013-12-15

This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right.

Mechanistic phenotypes: an aggregative phenotyping strategy to identify disease mechanisms using GWAS data.

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Jonathan D Mosley

Full Text Available A single mutation can alter cellular and global homeostatic mechanisms and give rise to multiple clinical diseases. We hypothesized that these disease mechanisms could be identified using low minor allele frequency (MAF<0.1 non-synonymous SNPs (nsSNPs associated with "mechanistic phenotypes", comprised of collections of related diagnoses. We studied two mechanistic phenotypes: (1 thrombosis, evaluated in a population of 1,655 African Americans; and (2 four groupings of cancer diagnoses, evaluated in 3,009 white European Americans. We tested associations between nsSNPs represented on GWAS platforms and mechanistic phenotypes ascertained from electronic medical records (EMRs, and sought enrichment in functional ontologies across the top-ranked associations. We used a two-step analytic approach whereby nsSNPs were first sorted by the strength of their association with a phenotype. We tested associations using two reverse genetic models and standard additive and recessive models. In the second step, we employed a hypothesis-free ontological enrichment analysis using the sorted nsSNPs to identify functional mechanisms underlying the diagnoses comprising the mechanistic phenotypes. The thrombosis phenotype was solely associated with ontologies related to blood coagulation (Fisher's p = 0.0001, FDR p = 0.03, driven by the F5, P2RY12 and F2RL2 genes. For the cancer phenotypes, the reverse genetics models were enriched in DNA repair functions (p = 2×10-5, FDR p = 0.03 (POLG/FANCI, SLX4/FANCP, XRCC1, BRCA1, FANCA, CHD1L while the additive model showed enrichment related to chromatid segregation (p = 4×10-6, FDR p = 0.005 (KIF25, PINX1. We were able to replicate nsSNP associations for POLG/FANCI, BRCA1, FANCA and CHD1L in independent data sets. Mechanism-oriented phenotyping using collections of EMR-derived diagnoses can elucidate fundamental disease mechanisms.

Phenotypic distance among assai palm’s mother plants (Euterpe oleracea Mart. from Eastern Amazon

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Rosemiro Santos Galate

2014-09-01

Full Text Available The açai palm tree (Euterpe oleracea Mart. is native to the Amazonian estuary. Media revelation of the nutraceutical properties of açai palm has resulted in its introduction in the national and international markets, consequently increasing the açai palm crop area in the Amazon. Nevertheless, açai palm cultivation is performed in a rational manner, because of limited product extraction from the native açai palm varieties. The study aimed to conduct a preliminary estimate of genetic variability, parameters, and phenotypic divergence of parent açai palms. Data from 129 parent plants from northeast Pará was collected. Analysis of variance (ANOVA of 22 morphoagronomic traits was performed to estimate the genetic parameters. Divergence was estimated using standardized average euclidean distance by using unweighted pair group method with arithmetic mean (UPGMA and Tocher clustering methods. Significant variance was noted in 77.3% traits (ANOVA, p<0.01 and p<0.05; CVg/CVe ratio indicated that 72.3% traits may present genetic variability for use in breeding programs. The euclidean distance showed EO-070 and EO-072 parent plants (Combu Island as the least divergent, and EO-010 (Belém and EO-018 (Salinópolis as the most divergent. The clustering methods determined ten (Tocher and nine (UPGMA similar groups. The most dissimilar parent plants were EO-035 (Capitão Poço, EO- 109 (Combu Island, EO-019 (Salinópolis, and EO-010 (Belém (Tocher method, whereas even the EO-010 (Belém; EO-011 (São João de Pirabas; EO-017, EO-018, and EO-019 (Salinópolis; EO-062 and EO-109 (Combu Island plants showed dissimilarity. We concluded that the 129 mother plants have high phenotypic variability, indicating the possibility of their use in genetic breeding programs. Further, the divergent parent plants can be used in the production of genotypes with favorable characteristics.

Genetic variability of environmental sensitivity revealed by phenotypic variation in body weight and (its correlations to physiological and behavioral traits.

Directory of Open Access Journals (Sweden)

Delphine Lallias

Full Text Available Adaptive phenotypic plasticity is a key component of the ability of organisms to cope with changing environmental conditions. Fish have been shown to exhibit a substantial level of phenotypic plasticity in response to abiotic and biotic factors. In the present study, we investigate the link between environmental sensitivity assessed globally (revealed by phenotypic variation in body weight and more targeted physiological and behavioral indicators that are generally used to assess the sensitivity of a fish to environmental stressors. We took advantage of original biological material, the rainbow trout isogenic lines, which allowed the disentangling of the genetic and environmental parts of the phenotypic variance. Ten lines were characterized for the changes of body weight variability (weight measurements taken every month during 18 months, the plasma cortisol response to confinement stress (3 challenges and a set of selected behavioral indicators. This study unambiguously demonstrated the existence of genetic determinism of environmental sensitivity, with some lines being particularly sensitive to environmental fluctuations and others rather insensitive. Correlations between coefficient of variation (CV for body weight and behavioral and physiological traits were observed. This confirmed that CV for body weight could be used as an indicator of environmental sensitivity. As the relationship between indicators (CV weight, risk-taking, exploration and cortisol was shown to be likely depending on the nature and intensity of the stressor, the joint use of several indicators should help to investigate the biological complexity of environmental sensitivity.

Portfolios Dominating Indices: Optimization with Second-Order Stochastic Dominance Constraints vs. Minimum and Mean Variance Portfolios

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Neslihan Fidan Keçeci

2016-10-01

Full Text Available The paper compares portfolio optimization with the Second-Order Stochastic Dominance (SSD constraints with mean-variance and minimum variance portfolio optimization. As a distribution-free decision rule, stochastic dominance takes into account the entire distribution of return rather than some specific characteristic, such as variance. The paper is focused on practical applications of the portfolio optimization and uses the Portfolio Safeguard (PSG package, which has precoded modules for optimization with SSD constraints, mean-variance and minimum variance portfolio optimization. We have done in-sample and out-of-sample simulations for portfolios of stocks from the Dow Jones, S&P 100 and DAX indices. The considered portfolios’ SSD dominate the Dow Jones, S&P 100 and DAX indices. Simulation demonstrated a superior performance of portfolios with SD constraints, versus mean-variance and minimum variance portfolios.

Phenotypic variation of larks along an aridity gradient : Are desert birds more flexible?

NARCIS (Netherlands)

Tieleman, BI; Williams, JB; Buschur, ME; Brown, CR

We investigated interindividual variation and intra-individual phenotypic flexibility in basal metabolic rate (BMR), total evaporative water loss (TEWL), body temperature (T-b), the minimum dry heat transfer coefficient (h), and organ and muscle size of five species of larks geographically

Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation.

Science.gov (United States)

Yang, Ye; Christensen, Ole F; Sorensen, Daniel

2011-02-01

Over recent years, statistical support for the presence of genetic factors operating at the level of the environmental variance has come from fitting a genetically structured heterogeneous variance model to field or experimental data in various species. Misleading results may arise due to skewness of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box-Cox transformations. Litter size data in rabbits and pigs that had previously been analysed in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box-Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected by the presence of asymmetry in the distribution of data. We recommend that to avoid one important source of spurious inferences, future work seeking support for a genetic component acting on environmental variation using a parametric approach based on normality assumptions confirms that these are met.

Methods to estimate the between‐study variance and its uncertainty in meta‐analysis†

Science.gov (United States)

Jackson, Dan; Viechtbauer, Wolfgang; Bender, Ralf; Bowden, Jack; Knapp, Guido; Kuss, Oliver; Higgins, Julian PT; Langan, Dean; Salanti, Georgia

2015-01-01

Meta‐analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between‐study variability, which is typically modelled using a between‐study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between‐study variance, has been long challenged. Our aim is to identify known methods for estimation of the between‐study variance and its corresponding uncertainty, and to summarise the simulation and empirical evidence that compares them. We identified 16 estimators for the between‐study variance, seven methods to calculate confidence intervals, and several comparative studies. Simulation studies suggest that for both dichotomous and continuous data the estimator proposed by Paule and Mandel and for continuous data the restricted maximum likelihood estimator are better alternatives to estimate the between‐study variance. Based on the scenarios and results presented in the published studies, we recommend the Q‐profile method and the alternative approach based on a ‘generalised Cochran between‐study variance statistic’ to compute corresponding confidence intervals around the resulting estimates. Our recommendations are based on a qualitative evaluation of the existing literature and expert consensus. Evidence‐based recommendations require an extensive simulation study where all methods would be compared under the same scenarios. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd. PMID:26332144

The role of respondents’ comfort for variance in stated choice surveys

DEFF Research Database (Denmark)

Emang, Diana; Lundhede, Thomas; Thorsen, Bo Jellesmark

2017-01-01

they complete surveys correlates with the error variance in stated choice models of their responses. Comfort-related variables are included in the scale functions of the scaled multinomial logit models. The hypothesis was that higher comfort reduces error variance in answers, as revealed by a higher scale...... parameter and vice versa. Information on, e.g., sleep and time since eating (higher comfort) correlated with scale heterogeneity, and produced lower error variance when controlled for in the model. That respondents’ comfort may influence choice behavior suggests that knowledge of the respondents’ activity......Preference elicitation among outdoor recreational users is subject to measurement errors that depend, in part, on survey planning. This study uses data from a choice experiment survey on recreational SCUBA diving to investigate whether self-reported information on respondents’ comfort when...

Suspected ontogeny of a recently described hypo-androgenic PCOS-like phenotype with advancing age.

Science.gov (United States)

Gleicher, Norbert; Kushnir, Vitaly A; Darmon, Sarah K; Wang, Qi; Zhang, Lin; Albertini, David F; Barad, David H

2018-03-01

A recent report described a new PCOS-like phenotype in lean older infertile women, and was characterized by high age-specific anti-Müllerian hormone (AMH) but hypo- rather than the expected hyper-androgenism. The hypo-androgenism was, furthermore, characterized of, likely, adrenal origin and autoimmune etiology. We extracted data on 708 consecutive infertility patients, and separated them into three age-strata, 42 years. In each stratum, we investigated how levels of anti-Müllerian hormone (AMH) and testosterone (T) interrelate between high-AMH (AMH ≥ 75th quantile) and normal AMH (25th-75th quantile) and low-T (total testosterone ≤19.0 ng/dL), normal-T (19.0-29.0 ng/dL) and high-T (>29.0 ng/dL). High-AMH cycles were presumed to reflect PCOS-like patients. Routine in vitro fertilization (IVF) cycle outcomes and clinical phenotypes of patients were then compared between groups with AMH and T as statistical variables. This hypo-androgenic PCOS-like phenotype already exists in age stratum androgenic PCOS phenotype that develops in comparison to controls (likely autoimmune-induced) insufficiency of the adrenal zona reticularis (low-T and low-DHEAS) and zona fasciculata (low-C), and is characterized by frequent evidence of autoimmunity. A degree of adrenal insufficiency, thus, concomitantly appears to affect adrenal androgen and, to lesser degrees, glucocorticoid production (mineralocorticoids were not investigated). Here investigated new PCOS-like phenotype demonstrates features compatible with what under Rotterdam criteria has been referred to as PCOS phenotype-D. If confirmed, the observation that the ontogeny of this phenotype already at young ages is, likely, driven by adrenal autoimmunity, supports the position of the androgen excess and PCOS society that the etiology of phenotype-D differs from that of classical hyper-androgenic PCOS of mostly ovarian etiology.

Phenotype prediction using regularized regression on genetic data in the DREAM5 Systems Genetics B Challenge.

Directory of Open Access Journals (Sweden)

Po-Ru Loh

Full Text Available A major goal of large-scale genomics projects is to enable the use of data from high-throughput experimental methods to predict complex phenotypes such as disease susceptibility. The DREAM5 Systems Genetics B Challenge solicited algorithms to predict soybean plant resistance to the pathogen Phytophthora sojae from training sets including phenotype, genotype, and gene expression data. The challenge test set was divided into three subcategories, one requiring prediction based on only genotype data, another on only gene expression data, and the third on both genotype and gene expression data. Here we present our approach, primarily using regularized regression, which received the best-performer award for subchallenge B2 (gene expression only. We found that despite the availability of 941 genotype markers and 28,395 gene expression features, optimal models determined by cross-validation experiments typically used fewer than ten predictors, underscoring the importance of strong regularization in noisy datasets with far more features than samples. We also present substantial analysis of the training and test setup of the challenge, identifying high variance in performance on the gold standard test sets.

[Total knee and hip prosthesis: variables associated with costs].

Science.gov (United States)

Herrera-Espiñeira, Carmen; Escobar, Antonio; Navarro-Espigares, José Luis; Castillo, Juan de Dios Lunadel; García-Pérez, Lidia; Godoy-Montijano, Amparo

2013-01-01

The elevated prevalence of osteoarthritis in Western countries, the high costs of hip and knee arthroplasty, and the wide variations in the clinical practice have generated considerable interest in comparing the associated costs before and after surgery. To determine the influence of a number of variables on the costs of total knee and hip arthroplasty surgery during the hospital stay and during the one-year post-discharge. A prospective multi-center study was performed in 15 hospitals from three Spanish regions. Relationships between the independent variables and the costs of hospital stay and postdischarge follow-up were analyzed by using multilevel models in which the "hospital" variable was used to group cases. Independent variables were: age, sex, body mass index, preoperative quality of life (SF-12, EQ-5 and Womac questionnaires), surgery (hip/knee), Charlson Index, general and local complications, number of beds and economic-institutional dependency of the hospital, the autonomous region to which it belongs, and the presence of a caregiver. The cost of hospital stay, excluding the cost of the prosthesis, was 4,734 Euros, and the post-discharge cost was 554 Euros. With regard to hospital stay costs, the variance among hospitals explained 44-46% of the total variance among the patients. With regard to the post-discharge costs, the variability among hospitals explained 7-9% of the variance among the patients. There is considerable potential for reducing the hospital stay costs of these patients, given that more than 44% of the observed variability was not determined by the clinical conditions of the patients but rather by the behavior of the hospitals.

Fluctuations in atomic collision cascades - variance and correlations in sputtering and defect distributions

International Nuclear Information System (INIS)

Chakarova, R.; Pazsit, I.

1997-01-01

Fluctuation phenomena are investigated in various collision processes, i.e. ion bombardment induced sputtering and defect creation. The mean and variance of the sputter yield and the vacancies and interstitials are calculated as functions of the ion energy and the ion-target mass ratio. It is found that the relative variance of the defects in half-spaces and the relative variance of the sputter yield are not monotonous functions of the mass ratio. Two-point correlation functions in the depth variable, as well as sputtered energy, are also calculated. These functions help interpreting the behaviour of the relative variances of the integrated quantities, as well as understanding the cascade dynamics. All calculations are based on Lindhard power-law cross sections and use a binary collision Monte Carlo algorithm. 30 refs, 25 figs

Fluctuations in atomic collision cascades - variance and correlations in sputtering and defect distributions

Energy Technology Data Exchange (ETDEWEB)

Chakarova, R.; Pazsit, I.

1997-01-01

Fluctuation phenomena are investigated in various collision processes, i.e. ion bombardment induced sputtering and defect creation. The mean and variance of the sputter yield and the vacancies and interstitials are calculated as functions of the ion energy and the ion-target mass ratio. It is found that the relative variance of the defects in half-spaces and the relative variance of the sputter yield are not monotonous functions of the mass ratio. Two-point correlation functions in the depth variable, as well as sputtered energy, are also calculated. These functions help interpreting the behaviour of the relative variances of the integrated quantities, as well as understanding the cascade dynamics. All calculations are based on Lindhard power-law cross sections and use a binary collision Monte Carlo algorithm. 30 refs, 25 figs.

On discrete stochastic processes with long-lasting time dependence in the variance

Science.gov (United States)

Queirós, S. M. D.

2008-11-01

In this manuscript, we analytically and numerically study statistical properties of an heteroskedastic process based on the celebrated ARCH generator of random variables whose variance is defined by a memory of qm-exponencial, form (eqm=1 x=ex). Specifically, we inspect the self-correlation function of squared random variables as well as the kurtosis. In addition, by numerical procedures, we infer the stationary probability density function of both of the heteroskedastic random variables and the variance, the multiscaling properties, the first-passage times distribution, and the dependence degree. Finally, we introduce an asymmetric variance version of the model that enables us to reproduce the so-called leverage effect in financial markets.

A Cure for Variance Inflation in High Dimensional Kernel Principal Component Analysis

DEFF Research Database (Denmark)

Abrahamsen, Trine Julie; Hansen, Lars Kai

2011-01-01

Small sample high-dimensional principal component analysis (PCA) suffers from variance inflation and lack of generalizability. It has earlier been pointed out that a simple leave-one-out variance renormalization scheme can cure the problem. In this paper we generalize the cure in two directions......: First, we propose a computationally less intensive approximate leave-one-out estimator, secondly, we show that variance inflation is also present in kernel principal component analysis (kPCA) and we provide a non-parametric renormalization scheme which can quite efficiently restore generalizability in kPCA....... As for PCA our analysis also suggests a simplified approximate expression. © 2011 Trine J. Abrahamsen and Lars K. Hansen....

Handling nonnormality and variance heterogeneity for quantitative sublethal toxicity tests.

Science.gov (United States)

Ritz, Christian; Van der Vliet, Leana

2009-09-01

The advantages of using regression-based techniques to derive endpoints from environmental toxicity data are clear, and slowly, this superior analytical technique is gaining acceptance. As use of regression-based analysis becomes more widespread, some of the associated nuances and potential problems come into sharper focus. Looking at data sets that cover a broad spectrum of standard test species, we noticed that some model fits to data failed to meet two key assumptions-variance homogeneity and normality-that are necessary for correct statistical analysis via regression-based techniques. Failure to meet these assumptions often is caused by reduced variance at the concentrations showing severe adverse effects. Although commonly used with linear regression analysis, transformation of the response variable only is not appropriate when fitting data using nonlinear regression techniques. Through analysis of sample data sets, including Lemna minor, Eisenia andrei (terrestrial earthworm), and algae, we show that both the so-called Box-Cox transformation and use of the Poisson distribution can help to correct variance heterogeneity and nonnormality and so allow nonlinear regression analysis to be implemented. Both the Box-Cox transformation and the Poisson distribution can be readily implemented into existing protocols for statistical analysis. By correcting for nonnormality and variance heterogeneity, these two statistical tools can be used to encourage the transition to regression-based analysis and the depreciation of less-desirable and less-flexible analytical techniques, such as linear interpolation.

Analysis of force variance for a continuous miner drum using the Design of Experiments method

Energy Technology Data Exchange (ETDEWEB)

S. Somanchi; V.J. Kecojevic; C.J. Bise [Pennsylvania State University, University Park, PA (United States)

2006-06-15

Continuous miners (CMs) are excavating machines designed to extract a variety of minerals by underground mining. The variance in force experienced by the cutting drum is a very important aspect that must be considered during drum design. A uniform variance essentially means that an equal load is applied on the individual cutting bits and this, in turn, enables better cutting action, greater efficiency, and longer bit and machine life. There are certain input parameters used in the drum design whose exact relationships with force variance are not clearly understood. This paper determines (1) the factors that have a significant effect on the force variance of the drum and (2) the values that can be assigned to these factors to minimize the force variance. A computer program, Continuous Miner Drum (CMD), was developed in collaboration with Kennametal, Inc. to facilitate the mechanical design of CM drums. CMD also facilitated data collection for determining significant factors affecting force variance. Six input parameters, including centre pitch, outer pitch, balance angle, shift angle, set angle and relative angle were tested at two levels. Trials were configured using the Design of Experiments (DoE) method where 2{sup 6} full-factorial experimental design was selected to investigate the effect of these factors on force variance. Results from the analysis show that all parameters except balance angle, as well as their interactions, significantly affect the force variance.

Paraoxonase 1 Phenotype and Mass in South Asian versus Caucasian Renal Transplant Recipients

Directory of Open Access Journals (Sweden)

Philip W. Connelly

2012-01-01

Full Text Available South Asian renal transplant recipients have a higher incidence of cardiovascular disease compared with Caucasian renal transplant recipients. We carried out a study to determine whether paraoxonase 1, a novel biomarker for cardiovascular risk, was decreased in South Asian compared with Caucasian renal transplant recipients. Subjects were matched two to one on the basis of age and sex for a total of 129 subjects. Paraoxonase 1 was measured by mass, arylesterase activity, and two-substrate phenotype assay. Comparisons were made by using a matched design. The frequency of PON1 QQ, QR and RR phenotype was 56%, 37%, and 7% for Caucasian subjects versus 35%, 44%, and 21% for South Asian subjects (χ2=7.72, P=0.02. PON1 mass and arylesterase activity were not significantly different between South Asian and Caucasian subjects. PON1 mass was significantly associated with PON1 phenotype (P=0.0001, HDL cholesterol (P=0.009, LDL cholesterol (P=0.02, and diabetes status (P<0.05. Arylesterase activity was only associated with HDL cholesterol (P=0.003. Thus the frequency of the PON1 RR phenotype was higher and that of the QQ phenotype was lower in South Asian versus Caucasian renal transplant recipients. However, ethnicity was not a significant factor as a determinant of PON1 mass or arylesterase activity, with or without analysis including PON1 phenotype. The two-substrate method for determining PON1 phenotype may be of value for future studies of cardiovascular complications in renal transplant recipients.

Paraoxonase 1 Phenotype and Mass in South Asian versus Caucasian Renal Transplant Recipients.

Science.gov (United States)

Connelly, Philip W; Maguire, Graham F; Nash, Michelle M; Rapi, Lindita; Yan, Andrew T; Prasad, G V Ramesh

2012-01-01

South Asian renal transplant recipients have a higher incidence of cardiovascular disease compared with Caucasian renal transplant recipients. We carried out a study to determine whether paraoxonase 1, a novel biomarker for cardiovascular risk, was decreased in South Asian compared with Caucasian renal transplant recipients. Subjects were matched two to one on the basis of age and sex for a total of 129 subjects. Paraoxonase 1 was measured by mass, arylesterase activity, and two-substrate phenotype assay. Comparisons were made by using a matched design. The frequency of PON1 QQ, QR and RR phenotype was 56%, 37%, and 7% for Caucasian subjects versus 35%, 44%, and 21% for South Asian subjects (χ(2) = 7.72, P = 0.02). PON1 mass and arylesterase activity were not significantly different between South Asian and Caucasian subjects. PON1 mass was significantly associated with PON1 phenotype (P = 0.0001), HDL cholesterol (P = 0.009), LDL cholesterol (P = 0.02), and diabetes status (P < 0.05). Arylesterase activity was only associated with HDL cholesterol (P = 0.003). Thus the frequency of the PON1 RR phenotype was higher and that of the QQ phenotype was lower in South Asian versus Caucasian renal transplant recipients. However, ethnicity was not a significant factor as a determinant of PON1 mass or arylesterase activity, with or without analysis including PON1 phenotype. The two-substrate method for determining PON1 phenotype may be of value for future studies of cardiovascular complications in renal transplant recipients.

78 FR 14122 - Revocation of Permanent Variances

Science.gov (United States)

2013-03-04

... Douglas Fir planking had to have at least a 1,900 fiber stress and 1,900,000 modulus of elasticity, while the Yellow Pine planking had to have at least 2,500 fiber stress and 2,000,000 modulus of elasticity... the permanent variances, and affected employees, to submit written data, views, and arguments...

Optimal control of LQG problem with an explicit trade-off between mean and variance

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Qian, Fucai; Xie, Guo; Liu, Ding; Xie, Wenfang

2011-12-01

For discrete-time linear-quadratic Gaussian (LQG) control problems, a utility function on the expectation and the variance of the conventional performance index is considered. The utility function is viewed as an overall objective of the system and can perform the optimal trade-off between the mean and the variance of performance index. The nonlinear utility function is first converted into an auxiliary parameters optimisation problem about the expectation and the variance. Then an optimal closed-loop feedback controller for the nonseparable mean-variance minimisation problem is designed by nonlinear mathematical programming. Finally, simulation results are given to verify the algorithm's effectiveness obtained in this article.