Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test-day milk yield (TDMY) from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

NDA waveform estimation in the low-SNR regime

This correspondence addresses the problem of nondata-aidedwaveform estimation for digital communications. Based on the unconditionalmaximum likelihood criterion, the main contribution of this correspondenceis the derivation of a closed-form solution to the waveform estimationproblem in the low signal-to-noise ratio regime. The proposed estimationmethod is based on the second-order statistics of the received signaland a clear link is established between maximum likelihood estimation andcorrelation matching techniques. Compression with the signal-subspace isalso proposed to improve the robustness against the noise and to mitigatethe impact of abnormals or outliers.

Intrinsic subspace convergence in TDD MIMO communication

In numerical linear algebra, students encounter earlythe iterative power method, which finds eigenvectors of a matrixfrom an arbitrary starting point through repeated normalizationand multiplications by the matrix itself. In practice, more sophisticatedmethods are used nowadays, threatening to make the powermethod a historical and pedagogic footnote. However, in the contextof communication over a time-division duplex (TDD) multipleinputmultiple-output (MIMO) channel, the power method takes aspecial position. It can be viewed as an intrinsic part of the uplinkand downlink communication switching, enabling estimationof the eigenmodes of the channel without extra overhead. Generalizingthe method to vector subspaces, communication in thesubspaces with the best receive and transmit signal-to-noise ratio(SNR) is made possible. In exploring this intrinsic subspace convergence(ISC), we show that several published and new schemes canbe cast into a common framework where all members benefit fromthe ISC.

Maximum likelihood estimation of position in GNSS

In this letter, we obtain the Maximum LikelihoodEstimator of position in the framework of Global NavigationSatellite Systems. This theoretical result is the basis of a completelydifferent approach to the positioning problem, in contrastto the conventional two-steps position estimation, consistingof estimating the synchronization parameters of the in-viewsatellites and then performing a position estimation with thatinformation. To the authors’ knowledge, this is a novel approachwhich copes with signal fading and it mitigates multipath andjamming interferences. Besides, the concept of Position–basedSynchronization is introduced, which states that synchronizationparameters can be recovered from a user position estimation. Weprovide computer simulation results showing the robustness ofthe proposed approach in fading multipath channels. The RootMean Square Error performance of the proposed algorithm iscompared to those achieved with state-of-the-art synchronizationtechniques. A Sequential Monte–Carlo based method is used todeal with the multivariate optimization problem resulting fromthe ML solution in an iterative way.

Production scheduling tools' evaluation in a global telecommunications and electronics company

Tutkimuksen päätavoite on arvioida, ovatko neljä ohjelmistovaihtoehtoa riittäviä tuotannon aikataulutuksen työkaluja ja mikä työkaluista sopii toimeksiantajayritykselle. Alatavoitteena on kuvata tuotannon aikataulutuksen nyky- ja tahtotila prosessimallinnuksen avulla, selvittää työkalun käyttäjätarpeet ja määritellä priorisoidut valintakriteerit työkalulle.Tutkimuksen teoriaosuudessa tutkitaan tuotannon aikataulutuksen logiikkaa ja haasteita. Työssä tarkastellaan aikataulutusohjelmiston valintaa rinnakkain prosessinmallinnuksen kanssa. Aikataulutusohjelmistovaihtoehdot ja metodit käyttäjätarpeiden selvittämiseksi käydään läpi. Empiriaosuudessa selvitetään tutkimuksen suhde toimeksiantajayrityksen strategiaan. Käyttäjätarpeet selvitetään haastattelujen avulla jaanalysoidaan QFD matriisin avulla. Toimeksiantajayrityksen tuotannon aikataulutuksen nyky- ja tahtotilaprosessit mallinnetaan, jotta ohjelmistojen sopivuutta, aikataulutusprosessia tukevana työkaluna voidaan arvioida.Tutkimustuloksena ovatpriorisoidut valintakriteerit aikataulutustyökalulle eli käyttäjätarpeista johdetut tärkeimmät toiminnalliset ominaisuudet, järjestelmätoimittaja-arvio sekä suositukset jatkotoimenpiteistä ja lisätutkimuksesta.

Monte Carlo Methods in Parameter Estimation of Nonlinear Models

Yksi keskeisimmistä tehtävistä matemaattisten mallien tilastollisessa analyysissä on mallien tuntemattomien parametrien estimointi. Tässä diplomityössä ollaan kiinnostuneita tuntemattomien parametrien jakaumista ja niiden muodostamiseen sopivista numeerisista menetelmistä, etenkin tapauksissa, joissa malli on epälineaarinen parametrien suhteen. Erilaisten numeeristen menetelmien osalta pääpaino on Markovin ketju Monte Carlo -menetelmissä (MCMC). Nämä laskentaintensiiviset menetelmät ovat viime aikoina kasvattaneet suosiotaan lähinnä kasvaneen laskentatehon vuoksi. Sekä Markovin ketjujen että Monte Carlo -simuloinnin teoriaa on esitelty työssä siinä määrin, että menetelmien toimivuus saadaan perusteltua. Viime aikoina kehitetyistä menetelmistä tarkastellaan etenkin adaptiivisia MCMC menetelmiä. Työn lähestymistapa on käytännönläheinen ja erilaisia MCMC -menetelmien toteutukseen liittyviä asioita korostetaan. Työn empiirisessä osuudessa tarkastellaan viiden esimerkkimallin tuntemattomien parametrien jakaumaa käyttäen hyväksi teoriaosassa esitettyjä menetelmiä. Mallit kuvaavat kemiallisia reaktioita ja kuvataan tavallisina differentiaaliyhtälöryhminä. Mallit on kerätty kemisteiltä Lappeenrannan teknillisestä yliopistosta ja Åbo Akademista, Turusta.

Estimation des crues extrêmes dans les Alpes suisses a l'aide d'un modèle hydrologique distribué

Les modèles hydrologiques développés pour les pluies extrêmes de type PMP sont difficiles à paramétrer en raison du manque de données disponibles pour ces évènements et de la complexité du terrain. Cet article présente les processus et les résultats de l'ajustement des paramètres pour un modèle hydrologique distribué. Ce modèle à une échelle fine a été développé pour l'estimation des crues maximales probables dans le cas d'une PMP. Le calcul effectué pour deux bassins versants test suisses et pour deux épisodes d'orages d'été concerne l'estimation des paramètres du modèle, divisé en deux groupes. La première concerne le calcul des vitesses des écoulements et l'autre la détermination de la capacité d'infiltration initiale et finale pour chaque type de sol. Les résultats validés avec l'équation de Nash montrent une bonne corrélation entre les débits simulés et ceux observés.

Effect of cocoa powder in the prevention of cardiovascular disease: biological, consumption and inflammatory biomarkers. A metabolomic approach

Numerous health benefits have been attributed to cocoa and its derived products in the last decade including antioxidant, anti-platelet and positive effects on lipid metabolism and vascular function. Inflammation plays a key role in the initiation and progression of atherosclerosis. However, cocoa feeding trials focused on inflammation are still rare and the results yielded are controversial. Health effects derived from cocoa consumption have been partly attributed to its polyphenol content, in particular of flavanols. Bioavailability is a key issue for cocoa polyphenols in order to be able to exert their biological activities. In the case of flavanols, bioavailability is strongly influenced by several factors, such as their degree of polymerization and the food matrix in which the polyphenols are delivered. Furthermore, gut has become an active site for the metabolism of procyanidins (oligomeric and polymeric flavanols). Estimation of polyphenol consumption or exposure is also a very challenging task in Food and Nutrition Science in order to correlate the intake of phytochemicals with in vivo health effects. In the area of nutrition, modern analytical techniques based on mass spectrometry are leading to considerable advances in targeted metabolite analysis and particularly in Metabolomics or global metabolite analysis. In this chapter we have summarized the most relevant results of our recent research on the bioavailability of cocoa polyphenols in humans and the effect of the matrix in which cocoa polyphenols are delivered considering both targeted analysis and a metabolomic approach. Furthermore, we have also summarized the effect of long-term consumption of cocoa powder in patients at high risk of cardiovascular disease (CVD) on the inflammatory biomarkers of atherosclerosis.

Estimation of glomerular filtration rate in hospitalized patients : are we overestimating renal function?

Estimer la filtration glomérulaire chez les personnes âgées, tout en tenant compte de la difficulté supplémentaire d'évaluer leur masse musculaire, est difficile et particulièrement important pour la prescription de médicaments. Le taux plasmatique de la creatinine dépend à la fois de la fraction d'élimination rénale et extra-rénale et de la masse musculaire. Actuellement, pour estimer là filtration glomérulaire différentes formules sont utilisées, qui se fondent principalement sur la valeur de la créatinine. Néanmoins, en raison de la fraction éliminée par les voies tubulaires et intestinales la clairance de la créatinine surestime généralement le taux de filtration glomérulaire (GFR). Le but de cette étude est de vérifier la fiabilité de certains marqueurs et algorithmes de la fonction rénale actuellement utilisés et d'évaluer l'avantage additionnel de prendre en considération la masse musculaire mesurée par la bio-impédance dans une population âgée (> 70 ans) et avec une fonction rénale chronique compromise basée sur MDRD eGFR (CKD stades lll-IV). Dans cette étude, nous comparons 5 équations développées pour estimer la fonction rénale et basées respectivement sur la créatinine sérique (Cockcroft et MDRD), la cystatine C (Larsson), la créatinine combinée à la bêta-trace protéine (White), et la créatinine ajustée à la masse musculaire obtenue par analyse de la bio-impédance (MacDonald). La bio-impédance est une méthode couramment utilisée pour estimer la composition corporelle basée sur l'étude des propriétés électriques passives et de la géométrie des tissus biologiques. Cela permet d'estimer les volumes relatifs des différents tissus ou des fluides dans le corps, comme par exemple l'eau corporelle totale, la masse musculaire (=masse maigre) et la masse grasse corporelle. Nous avons évalué, dans une population âgée d'un service interne, et en utilisant la clairance de l'inuline (single shot) comme le « gold standard », les algorithmes de Cockcroft (GFR CKC), MDRD, Larsson (cystatine C, GFR CYS), White (beta trace protein, GFR BTP) et Macdonald (GFR = ALM, la masse musculaire par bio-impédance. Les résultats ont montré que le GFR (mean ± SD) mesurée avec l'inuline et calculée avec les algorithmes étaient respectivement de : 34.9±20 ml/min pour l'inuline, 46.7±18.5 ml/min pour CKC, 47.2±23 ml/min pour CYS, 54.4±18.2ml/min pour BTP, 49±15.9 ml/min pour MDRD et 32.9±27.2ml/min pour ALM. Les courbes ROC comparant la sensibilité et la spécificité, l'aire sous la courbe (AUC) et l'intervalle de confiance 95% étaient respectivement de : CKC 0 68 (055-0 81) MDRD 0.76 (0.64-0.87), Cystatin C 0.82 (0.72-0.92), BTP 0.75 (0.63-0.87), ALM 0.65 (0.52-0.78). ' En conclusion, les algorithmes comparés dans cette étude surestiment la GFR dans la population agee et hospitalisée, avec des polymorbidités et une classe CKD lll-IV. L'utilisation de l'impédance bioelectrique pour réduire l'erreur de l'estimation du GFR basé sur la créatinine n'a fourni aucune contribution significative, au contraire, elle a montré de moins bons résultats en comparaison aux autres equations. En fait dans cette étude 75% des patients ont changé leur classification CKD avec MacDonald (créatinine et masse musculaire), contre 49% avec CYS (cystatine C), 56% avec MDRD,52% avec Cockcroft et 65% avec BTP. Les meilleurs résultats ont été obtenus avec Larsson (CYS C) et la formule de Cockcroft.

Quantile Estimation in Non-Stationary Streaming Data

We provide an incremental quantile estimator for Non-stationary Streaming Data. We propose a method for simultaneous estimation of multiple quantiles corresponding to the given probability levels from streaming data. Due to the limitations of the memory, it is not feasible to compute the quantiles by storing the data. So estimating the quantiles as the data pass by is the only possibility. This can be effective in network measurement. To provide the minimum of the mean-squared error of the estimation, we use parabolic approximation and for comparison we simulate the results for different number of runs and using both linear and parabolic approximations.

Concentrations of resveratrol and derivatives in foods and estimation of dietary intake in a Spanish population: European Prospective Investigation into Cancer and Nutrition (EPIC)-Spain cohort

Resveratrol has been shown to have beneficial effects on diseases related to oxidant and/or inflammatory processes and extends the lifespan of simple organisms including rodents. The objective of the present study was to estimate the dietary intake of resveratrol and piceid (R&P) present in foods, and to identify the principal dietary sources of these compounds in the Spanish adult population. For this purpose, a food composition database (FCDB) of R&P in Spanish foods was compiled. The study included 40 685 subjects aged 3564 years from northern and southern regions of Spain who were included in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Spain cohort. Usual food intake was assessed by personal interviews using a computerised version of a validated diet history method. An FCDB with 160 items was compiled. The estimated median and mean of R&P intake were 100 and 933 mg/d respectively. Approximately, 32% of the population did not consume RΠ The most abundant of the four stilbenes studied was trans-piceid (53·6 %), followed by trans-resveratrol (20·9 %), cis-piceid (19·3 %) and cis-resveratrol (6·2 %). The most important source of R&P was wines (98·4 %) and grape and grape juices (1·6 %), whereas peanuts, pistachios and berries contributed to less than 0·01 %. For this reason the pattern of intake of R&P was similar to the wine pattern. This is the first time that R&P intake has been estimated in a Mediterranean country.

Genome-wide prediction of matrix attachment regions that increase gene expression in mammalian cells.

Gene transfer in eukaryotic cells and organisms suffers from epigenetic effects that result in low or unstable transgene expression and high clonal variability. Use of epigenetic regulators such as matrix attachment regions (MARs) is a promising approach to alleviate such unwanted effects. Dissection of a known MAR allowed the identification of sequence motifs that mediate elevated transgene expression. Bioinformatics analysis implied that these motifs adopt a curved DNA structure that positions nucleosomes and binds specific transcription factors. From these observations, we computed putative MARs from the human genome. Cloning of several predicted MARs indicated that they are much more potent than the previously known element, boosting the expression of recombinant proteins from cultured cells as well as mediating high and sustained expression in mice. Thus we computationally identified potent epigenetic regulators, opening new strategies toward high and stable transgene expression for research, therapeutic production or gene-based therapies.

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

Different concentrations of Mg++ ions affect nuclear matrix protein distribution during thermal stabilization of isolated nuclei.

The nuclear matrix, a proteinaceous network believed to be a scaffolding structure determining higher-order organization of chromatin, is usually prepared from intact nuclei by a series of extraction steps. In most cell types investigated the nuclear matrix does not spontaneously resist these treatments but must be stabilized before the application of extracting agents. Incubation of isolated nuclei at 37C or 42C in buffers containing Mg++ has been widely employed as stabilizing agent. We have previously demonstrated that heat treatment induces changes in the distribution of three nuclear scaffold proteins in nuclei prepared in the absence of Mg++ ions. We studied whether different concentrations of Mg++ (2.0-5 mM) affect the spatial distribution of nuclear matrix proteins in nuclei isolated from K562 erythroleukemia cells and stabilized by heat at either 37C or 42C. Five proteins were studied, two of which were RNA metabolism-related proteins (a 105-kD component of splicing complexes and an RNP component), one a 126-kD constituent of a class of nuclear bodies, and two were components of the inner matrix network. The localization of proteins was determined by immunofluorescent staining and confocal scanning laser microscope. Mg++ induced significant changes of antigen distribution even at the lowest concentration employed, and these modifications were enhanced in parallel with increase in the concentration of the divalent cation. The different sensitivity to heat stabilization and Mg++ of these nuclear proteins might reflect a different degree of association with the nuclear scaffold and can be closely related to their functional or structural role.