Normal Variance Research Articles

Staged Reconstruction for Malunited Fractures of the Distal Radius

This prospective study assessed the outcomes of 26 symptomatic malunited distal radial fractures which were treated with an opening wedge corrective osteotomy and bone grafting with rigid fixation. An ulnar shortening osteotomy was subsequently required as a second-stage operation in five cases to restore normal ulnar variance. A wrist arthroscopy was indicated as a third stage procedure with persistent ulnar sided wrist pain in order to address central tears of the triangular fibrocartilage. Satisfactory functional scores were achieved by 20 of the 26 patients after distal radial osteotomy alone and, 24 of the 26 after subsequent ulnar shortening osteotomies and arthroscopy when necessary. The one, two or three stage concept of reconstructing the malunited distal end radius could optimise the outcome rather than using a single-stage strategy.

Heritability of Hemostasis Phenotypes and Their Correlation with Type 2 Diabetes Status in Mexican Americans

Hypercoagulation often occurs in type 2 diabetes, suggesting pleiotropy of the genes that influence disease liability and hemostasis-related phenotypes. To better understand the relationship between hemostasis and diabetes, we first used maximum-likelihood methods to estimate the relative contribution of additive genetic, measured environmental, and shared household effects to the normal variance of 16 hemostasis-related traits in 813 individuals participating in the San Antonio Family Heart Study. We estimated moderate to high heritabilities (0.20-0.60) for each phenotype. Von Willebrand factor (VWF), thrombin activatable fibrinolysis inhibitor, activated protein C (APC) ratio, factor V, and prothrombin time had heritabilities greater than 0.50. The correlation between type 2 diabetes status and the hemostasis-related traits was then partitioned into genetic and environmental components using bivariate variance-components methods. Significant (p < or = 0.05) positive genetic correlations (0.37-0.51) occurred with factors II and VIII, VWF, total protein S (tPS), and tissue factor pathway inhibitor. Significant negative genetic correlations were estimated for activated partial thromboplastin time (-0.49) and APC ratio (-0.38). By contrast, significant environmental correlations occurred only with factor II (-0.40) and tPS (-0.31). Our results suggest that genes are important contributors to the normal variation in hemostasis-related traits and that genes influencing hemostasis-related traits pleiotropically influence diabetes risk.

Assessment of internal quality attributes of mandarin fruit. 1. NIR calibration model development

The utility of near infrared spectroscopy as a non-invasive technique for the assessment of internal eating quality parameters of mandarin fruit (Citrus reticulata cv. Imperial) was assessed. The calibration procedure for the attributes of TSS (total soluble solids) and DM (dry matter) was optimised with respect to a reference sampling technique, scan averaging, spectral window, data pre-treatment (in terms of derivative treatment and scatter correction routine) and regression procedure. The recommended procedure involved sampling of an equatorial position on the fruit with 1 scan per spectrum, and modified partial least squares model development on a 720–950-nm window, pre-treated as first derivative absorbance data (gap size of 4 data points) with standard normal variance and detrend scatter correction. Calibration model performance for the attributes of TSS and DM content was encouraging (typical Rc2 of &gt;0.75 and 0.90, respectively; typical root mean squared standard error of calibration of &lt;0.4 and 0.6%, respectively), whereas that for juiciness and total acidity was unacceptable. The robustness of the TSS and DM calibrations across new populations of fruit is documented in a companion study.

Neurocognitive correlates of socioeconomic status in kindergarten children

Socioeconomic status (SES) is strongly associated with cognitive ability and achievement during childhood and beyond. Little is known about the developmental relationships between SES and specific brain systems or their associated cognitive functions. In this study we assessed neurocognitive functioning of kindergarteners from different socioeconomic backgrounds, using tasks drawn from the cognitive neuroscience literature in order to determine how childhood SES predicts the normal variance in performance across different neurocognitive systems. Five neurocognitive systems were examined: the occipitotemporal/visual cognition system, the parietal/spatial cognition system, the medial temporal/memory system, the left perisylvian/language system, and the prefrontal/executive system. SES was disproportionately associated with the last two, with low SES children performing worse than middle SES children on most measures of these systems. Relations among language, executive function, SES and specific aspects of early childhood experience were explored, revealing intercorrelations and a seemingly predominant role of individual differences in language ability involved in SES associations with executive function.

On a class of improved estimators of variance and estimation under order restriction

We consider the estimation of error variance and construct a class of estimators improving upon the usual estimators uniformly under entropy loss or under squared error loss. Through a Monte Carlo simulation study, the magnitude of the risk reduction of our improved estimator as compared with the usual one is examined in a context of a nested linear hypothesis testing of a linear regression model, where substantial risk reduction can be attained. We also construct a class of confidence intervals having larger coverage probabilities and not larger interval lengths than those of the usual ones. This allows us to construct a class of estimators universally dominating the usual ones. Further, we consider the estimation of order-restricted normal variances. We give a class of isotonic regression estimators improving upon the usual ones under various types of order restrictions. We also give a class of improved confidence intervals over the usual ones, and a class of estimators universally dominating the usual ones.

Confirmation of a New Statistical Method for Comprehensively Dissecting QTLs Using In Vitro Transcription, the Model Factor VII Gene and a Novel Modification of the G-Free Cassette.

Thrombosis is a genetically complex disorder that plays a prominent pathogenic role in myocardial infarction, stroke and pulmonary embolism. Because these distinct endpoints of cardiovascular disease are the most common cause of death worldwide, the goal of investigators in several countries is to comprehensively catalogue human DNA polymorphisms influencing thrombosis susceptibility. It is now generally accepted that accomplishing this goal will require the use of linkage analysis and individuals from extended-pedigrees, even though previous investigations -- which predominantly were based on association analyses and case/control candidate gene studies -- resulted in several notable discoveries including the factor V Leiden mutation. In this regard, we recently completed the first genome linkage screen for DNA regions affecting normal variance of factor VII activity (fVII:C) levels in the 21 families from the Genetic Analysis of Idiopathic Thrombophilia (GAIT) Project. Only one quantitative trait locus (QTL) (LOD score=3.2; p-value=0.022) was identified and localized to the region of chr13q containing the fVII gene, F7. We performed the first comprehensive variation scan of this locus by resequencing the F7 genes in 40 unrelated GAIT subjects. The 49 polymorphisms identified were then genotyped in the full GAIT Project. Using a newly developed BQTN (Bayesian Quantitative Trait Nucleotide) method to estimate the posterior probability of a given variant being functional, we identified strong evidence for the functionality of 2 rare variants, including a novel SNP in intron 7 (C9830T) and a previously known SNP in the coding region of exon 8 (A294V). We also found 2 clusters of promoter (P) and intron 1 (I1) polymorphisms, designated C1: {A-630C, G-402A, T700C, G707A} and C2 {C-2989A, G-401T, -323ins0/10, T-122C, G73A, T835C}, within which all variants exhibit strong linkage disequilibrium (LD) and posterior probabilities of >90% for affecting fVII:C levels. In this study, we will use in vitro transcription to test the statistical findings of the BQTN analysis and, if confirmed, to specifically delineate the functional variant(s) in each cluster. We are creating G-free cassette (GfC) reporter constructs representing the natural P/I1 haplotypes statistically predicted as functional and 10 pairs of constructs where each pair represents the 2 alleles of each of the 10 variants in C1 and C2. All constructs have the same size P (0.9kb) and I1 (1kb) fragments ligated 5′ and 3′ of the GfC, respectively. Because C1 and C2 contain P and I1 variants, a new 120bp GfC was made to match the size of exon 1a and to approximate the native spacing of these polymorphisms in vivo. Once these constructs are sequenced, we will measure and compare their rate of transcriptional initiation using mouse liver nuclear extracts. Because of the strong LD among these P and I1 polymorphisms, population studies alone essentially only analyze the natural haplotypes that are present. The in vitro assays developed in this study will allow the specific influence of each polymorphism to be investigated in the context of a near native configuration of these known regulatory regions.

Fractures comminutives du radius distal traitées par ostéosynthèse et substitut osseux injectable: Étude prospective de 39 cas

Purpose of the study Comminution is often neglected in patients presenting fractures of the distal radius. Use of injectable bone substitutes can fill the gap left by comminution, avoiding radial shortening and loss of prono-supination. Material and methods Forty-eight patients with a distal fracture of the radius were treated by osteosynthesis and injectable cement between 1998 and 2001. These patients were reviewed at mean follow-up of 46 months (36-56). Dorsal displacement was present in all cases and the AO classification was A (n=26), B (n=15), C (n=7). Fixation was achieved with pins (n=32), posterior plate (n=14), and external fixator (n=2) before injection of the bone substitute. Outcome was evaluated with the Herzberg score, the Gartland and Werley score and DASH by an independent operator. Results Four patients were lost to follow-up and five who developed a deformed callus after the initial osteosynthesis were excluded from the analysis. The Herzberg functional score reached 84 (range 54-100) and the Gartland and Werley radioclinical score was 4.6 (0-11) with 89% excellent and good outcomes. DASH was 23.6 (5.8-62.7). Ulnar variance was unchanged or changed less than 2 mm between the immediate postoperative period and last follow-up in 88% of patients. There was one carpal tunnel syndrome related to anterior cement leakage. Three biopsies were performed and revealed a “humid sand” aspect six months after injection as well as presence of osteoblasts within the bone substitute. There was no or very little resorption. Discussion Several authors have demonstrated the biomechanical and functional effects of filling the comminution gap to avoid radial shortening. The first reported cases, then later prospective series, favored the use of injectable cements for patients with comminution. Cement used in our patients allowed preservation enables preservation of normal ulnar variance in addition to filling the gap. Like any bone substitute, it is an attractive alternative to other filling methods (ceramic graft) offering two advantages: adaptation to the bone defect and primary stability. This easy-to-use cement is resorbed slowly. Because of high cost, it may be reserved for patients with important functional needs.

Near Infrared Reflectance Spectroscopy of Oil in Intact Canola Seed (Brassica Napus, L.). I. Attributes of the Intact Seed Spectrum

This study examined the attributes of the oil signal embedded in the near infrared (NIR) reflectance spectra of intact canola seed. The oil/spectrum relationship was examined with the aid of the following techniques: comparison of raw log 1/ R spectra, investigation of absorption difference spectra and investigation of oil/wavelength correlations. The 1100–2500 nm reflectance spectrum of canola oil contains three major segments, 1150 to 1250 nm, 1650 to 1800 nm and 2250 to 2380 nm, that denote absorption of the constituent. The spectrum of intact canola seed closely resembles the spectrum of oil. However, the strength of oil absorption in the seed is significantly reduced, particularly at the longer wavelengths. Examination of the NIR spectra revealed that the oil signal embedded in the reflectance spectrum of intact canola seed was primarily affected by the spectral characteristics of the seed. Signal correction tools—standard normal variance, detrending and the second order derivative—applied to the data showed an unreliable efficiency in minimising scattering defects in the spectra. The absorption difference spectra displayed variable patterns in the manifestation of differences in the oil concentration between canola samples. These differences could be observed either in all or only in some of the oil-specific segments of the spectrum. Correlograms illustrated a very complex spectrum/oil relationship, displaying a large number of wavelengths strongly correlated to the oil across the entire 1100–2500 nm spectrum, including a considerable number of wavelengths, which displayed chance correlations. Therefore, NIR analysis of oil in the intact canola seed preferably should involve the full spectrum information and should involve the use of latent variables, rather than the original wavelength space.

Extracting the Dark Matter Profile of a Relaxed Galaxy Cluster

Knowledge of the structure of galaxy clusters is essential for an understanding of large-scale structure in the universe and may provide important clues to the nature of dark matter. Moreover, the shape of the dark matter distribution in the cluster core may offer insight into the structure formation process. Unfortunately, cluster cores also tend to be the site of complicated astrophysics. X-ray imaging spectroscopy of relaxed clusters, a standard technique for mapping their dark matter distributions, is often complicated by the presence of cool components in cluster cores, and the dark matter profile one derives for a cluster is sensitive to assumptions made about the distribution of this component. In addition, fluctuations in the temperature measurements resulting from normal statistical variance can produce results that are unphysical. We present here a procedure for extracting the dark matter profile of a spherically symmetric, relaxed galaxy cluster that deals with both of these complications. We apply this technique to a sample of galaxy clusters observed with the Chandra X-Ray Observatory and comment on the resulting mass profiles. For some of the clusters we compare their masses with those derived from weak and strong gravitational measurements.

Parameter Optimisation Modeling Using Stationary 1D-Electrothermal Model to Improve Temperature Homogeneity

A parameter optimisation model is developed to find the parameters that have significant effects on homogeneous temperature distribution during microwave processing of materials. Electromagnetic, thermal and processing parameters are collected for a wide variety of materials and the heating profiles are calculated using a stationary 1D-electrothermal model. A measure of temperature homogeneity is obtained from the heating profiles by statistical calculations of normalised variance (the response variable). The processing parameters (power, temperature, size of the material sample) are optimised for all of these materials for a minimum normalised variance which allows maximum change of ± 3% Taverage on the T-distribution to meet most of the industrial process requirements. This mathematical model suggests a group of materials, which requires modifications in processing conditions to achieve uniform heating.

A novel approach to determine normal variation in gene expression data

Animal models for human diseases are of crucial importance for studying gene expression and regulation. In the last decade the development of mouse models for cancer, diabetes, neuro-degenerative and many other diseases has been on steady rise. Microarray analysis of patterns of gene expression in mouse models of various pathological types and the study of molecular level changes as a result of interventions, holds lot of promise to the understanding of biological processes involved. The genes which show normal variance across genetically identical mice are of particular interest because they could serve as a databank for possible false positives in gene expression studies in similar kind of mice. Also they could provide useful insights into the biological processes behind the differential expression patterns in otherwise similar mice. Our approach systematically removes variance due to experimental noise in each of the mice and then mines for normal variance among the identical mice. This analysis carried over six tissues sampled from mice, resulted in several genes which showed variations among identical mice, thus enabling a comprehensive database of normal variations in gene expression for mouse models. A large number of these genes are known to be related to stress response, hypertension and heat shock. Also Principal Component Analysis was done to visualize similarity among the mice models and within the replicates. These studies help in the design of gene expression studies in mouse models and help in validation of the results.

A semi-parametric approach to risk management

The benchmark theory of mathematical finance is the Black–Scholes–Merton (BSM) theory, based on Brownian motion as the driving noise process for stock prices. Here the distributions of financial returns of the stocks in a portfolio are multivariate normal. Risk management based on BSM underestimates tails. Hence estimation of tail behaviour is often based on extreme value theory (EVT). Here we discuss a semi-parametric replacement for the multivariate normal involving normal variance–mean mixtures. This allows a more accurate modelling of tails, together with various degrees of tail dependence, while (unlike EVT) the whole return distribution can be modelled. We use a parametric component, incorporating the mean vector μ and covariance matrix Σ, and a non-parametric component, which we can think of as a density on [0,∞), modelling the shape (in particular the tail decay) of the distribution. We work mainly within the family of elliptically contoured distributions, focusing particularly on normal variance mixtures with self-decomposable mixing distributions. We discuss efficient methods to estimate the parametric and non-parametric components of our model and provide an algorithm for simulating from such a model. We fit our model to several financial data series. Finally, we calculate value at risk (VaR) quantities for several portfolios and compare these VaRs to those obtained from simple multivariate normal and parametric mixture models.

Empirical Bayesian estimation of normal variances and covariances

This paper derives and evaluates an algorithm for estimating normal covariances. A particular concern is the performance of the estimator when the dimension of the space exceeds the number of observations. The algorithm is simple, tolerably well founded, and seems to be more accurate for its purpose than the alternatives. Other topics discussed are the joint estimation of variances in one and many dimensions; the loss function appropriate to a variance estimator; and its connection with a certain Bayesian prescription.

Bias and the Power Spectrum beyond the Turnover

Threshold biasing of a Gaussian random field gives a linear amplification of the reduced two point correlation function at large distances. We show that for standard cosmological models this does not translate into a linear amplification of the power spectrum (PS) at small k. For standard CDM type models this means that the ``turn-over'' at small k of the original PS disappears in the PS of the biased field for the physically relevant range of the threshold parameter \nu. In real space this difference is manifest in the asymptotic behaviour of the normalised mass variance in spheres of radius R, which changes from the ``super-homogeneous'' behaviour \sigma^2(R) \sim R^{-4} to a Poisson-like behaviour \sigma^2 {\nu}(R) \sim R^{-3}. This qualitative change results from the intrinsic stochasticity of the threshold sampling. While our quantitative results are specific to the simplest threshold biasing model, we argue that our qualitative conclusions should be valid generically for any biasing mechanism involving a scale-dependent amplification of the correlation function. One implication is that the real-space correlation function will be a better instrument to probe for the underlying Harrison Zeldovich spectrum in the distribution of visible matter, as the characteristic asymptotic negative power-law \xi (r) \sim -r^{-4} tail is undistorted by biasing.

情報科学の展開とＤＤＳ ゲノムインフォマテックスと治療の最適化

The Human Genome Project is now almost completed, and we are now about to move into the post-genome sequence era of Functional Genomics. The advent of genome science had markedly changed the way how the life science research including medical study is conducted ; thus, systematic and integrated, “genome-wide” survey is feasible, Human Genome Project provides insights so profound that it has the ability to change everything we know about medicine and how medicines are developed. Genetic factors contribute substantially to variable drug effects and constitute a critical element of a product's profile that must be considered in clinical use. Pharmacogenomics is a rapidly emerging field focused on understanding the genetic factors underlying drug action and applying this information to improve the clinical use and development of pharmaceutical products. In clinical practice, the understanding of how genetic variation leads to variable drug effects can be used to prescribe drugs selectively to individuals in regimens and doses that are most likely to be safe and effective (Personalized Medicine). Also, pharmacogenomics will promote to develop novel pharmaceutical products targeted to the normal genetic variance of human populations. In drug development, knowledge of genetic variation that may affect drug action can be used to reduce the cost and complexity of clinical trials, increase the success rate of achieving regulatory approval, and achieve approvals for new classes of diagnostic and therapeutic products. Pharmacogenomics programs, thus, enhances the development, commercialization, and clinical use of conventional pharmaceutical products for common diseases, and eventually a powerful tool for Evidence-Based Medicine.

2001 Bhuj, India, Earthquake Engineering Seismoscope Recordings and Eastern North America Ground-Motion Attenuation Relations

Engineering seismoscope data collected at distances less than 300 km for the M 7.7 Bhuj, India, mainshock are compatible with ground-motion attenuation in eastern North America (ENA). The mainshock ground-motion data have been corrected to a common geological site condition using the factors of Joyner and Boore (2000) and a classification scheme of Quaternary or Tertiary sediments or rock. We then compare these data to ENA ground-motion attenuation relations. Despite uncertainties in recording method, geological site corrections, common tectonic setting, and the amount of regional seismic attenuation, the corrected Bhuj dataset agrees with the collective predictions by ENA ground-motion attenuation relations within a factor of 2. This level of agreement is within the dataset uncertainties and the normal variance for recorded earthquake ground motions.

Improved confidence estimators for the usual one-sided confidence intervals for the ratio of two normal variances

The usual confidence intervals for the ratio of two normal variances are constructed from F-distribution. These confidence intervals are especially important in the variance component model. In this paper, I focus on confidence estimate and conditional performance of these confidence intervals. Under some conditions, confidence estimators better than the confidence coefficient are provided in this article. Moreover, conditional properties of these intervals are also discussed.

Semi-parametric modelling in finance: theoretical foundations

The benchmark theory of mathematical finance is the Black-Scholes-Merton theory, based on Brownian motion as the driving noise process for asset prices. Here the distributions of returns of the assets in a portfolio are multivariate normal. The two most obvious limitations here concern symmetry and thin tails, neither being consistent with real data. The most common replacements for the multinormal are parametric—stable, generalized hyperbolic, variance gamma. In this paper we advocate the use of semi-parametric models for distributions, where the mean vector μ and covariance Σ are parametric components and the so-called density generator (function) g is the non-parametric component. We work mainly within the family of elliptically contoured distributions, focusing particularly on normal variance mixtures with self-decomposable mixing distributions. We show how the parametric cases can be treated in a unified, systematic way within the non-parametric framework and obtain the density generators for the most important cases.

INTRINSIC PRIORS FOR TWO-SAMPLE TESTS IN NORMAL POPULATIONS

ABSTRACT There have been considerable amounts of work regarding the development of various default Bayes factors in model selection and hypothesis testing. Two commonly used criteria, the intrinsic Bayes factor and the fractional Bayes factor are compared to test two independent normal means and variances. We also derive several intrinsic priors whose Bayes factors are asymptotically equivalent to the respective Bayes factors. We demonstrate our results in simulated datasets.

Existence of the uniformly minimum risk equivariant estimators of parameters in a class of normal linear models

In this paper, we study the existence of the uniformly minimum risk equivariant (UMRE) estimators of parameters in a class of normal linear models, which include the normal variance components model, the growth curve model, the extended growth curve model, and the seemingly unrelated regression equations model, and so on. The necessary and sufficient conditions are given for the existence of UMRE estimators of the estimable linear functions of regression coefficients, the covariance matrix V and (tr V ) α , where α > 0 is known, in the models under an affine group of transformations for quadratic losses and matrix losses, respectively. Under the (extended) growth curve model and the seemingly unrelated regression equations model, the conclusions given in literature for estimating regression coefficients can be derived by applying the general results in this paper, and the sufficient conditions for non-existence of UMRE estimators of V and tr( V ) are expanded to be necessary and sufficient conditions. In addition, the necessary and sufficient conditions that there exist UMRE estimators of parameters in the variance components model are obtained for the first time.