Honey, I shrunk the sample covariance matrix

The central message of this paper is that nobody should be using the samplecovariance matrix for the purpose of portfolio optimization. It containsestimation error of the kind most likely to perturb a mean-varianceoptimizer. In its place, we suggest using the matrix obtained from thesample covariance matrix through a transformation called shrinkage. Thistends to pull the most extreme coefficients towards more central values,thereby systematically reducing estimation error where it matters most.Statistically, the challenge is to know the optimal shrinkage intensity,and we give the formula for that. Without changing any other step in theportfolio optimization process, we show on actual stock market data thatshrinkage reduces tracking error relative to a benchmark index, andsubstantially increases the realized information ratio of the activeportfolio manager.

The effects of milk as a food matrix for polyphenols on the excretion profile of cocoa (-)-Epicatechin metabolites in healthy humans subjects

The effect of different food matrices on the metabolism and excretion of polyphenols is uncertain. The objective of the study was to evaluate the possible effect of milk on the excretion of (2)-epicatechin metabolites from cocoa powder after its ingestion with and without milk. Twenty-one volunteers received the following three test meals each in a randomised cross-over design with a 1-week interval between meals: (1) 250 ml whole milk as a control; (2) 40 g cocoa powder dissolved in 250 ml whole milk (CC-M); (3) 40 g cocoa powder dissolved in 250 ml water (CC-W). Urine was collected before consumption and during the 0-6, 6-12 and 12-24 h periods after consumption. (2)-Epicatechin metabolite excretion was measured using liquid chromatography-MS. One (2)-epicatechin glucuronide and three (2)-epicatechin sulfates were detected in urine excreted after the intake of the two cocoa beverages (CC-M and CC-W). The results show that milk does not significantly affect the total amount of metabolites excreted in urine. However, differences in metabolite excretion profiles were observed; there were changes in the glucuronide and sulfate excretion rates, and the sulfation position between the period of excretion and the matrix. The matrix in which polyphenols are consumed can affect their metabolism and excretion, and this may affect their biological activity. Thus, more studies are needed to evaluate the effect of these different metabolite profiles on the body.

How to use the standard model with own data?

In this work discuss the use of the standard model for the calculation of the solvency capital requirement (SCR) when the company aims to use the specific parameters of the model on the basis of the experience of its portfolio. In particular, this analysis focuses on the formula presented in the latest quantitative impact study (2010 CEIOPS) for non-life underwriting premium and reserve risk. One of the keys of the standard model for premium and reserves risk is the correlation matrix between lines of business. In this work we present how the correlation matrix between lines of business could be estimated from a quantitative perspective, as well as the possibility of using a credibility model for the estimation of the matrix of correlation between lines of business that merge qualitative and quantitative perspective.

The implementation of liquid chromatography tandem mass spectrometry for the official control of lipophilic toxins in seafood: Single-laboratory validation under four chromatographic conditions

We performed a comprehensive study to assess the fit for purpose of four chromatographic conditions for the determination of six groups of marine lipophilic toxins (okadaic acid and dinophysistoxins, pectenotoxins, azaspiracids, yessotoxins, gymnodimine and spirolides) by LC-MS/MS to select the most suitable conditions as stated by the European Union Reference Laboratory for Marine Biotoxins (EURLMB). For every case, the elution gradient has been optimized to achieve a total run-time cycle of 12 min. We performed a single-laboratory validation for the analysis of three relevant matrices for the seafood aquaculture industry (mussels, pacific oysters and clams), and for sea urchins for which no data about lipophilic toxins have been reported before. Moreover, we have compared the method performance under alkaline conditions using two quantification strategies: the external standard calibration (EXS) and the matrix-matched standard calibration (MMS). Alkaline conditions were the only scenario that allowed detection windows with polarity switching in a 3200 QTrap mass spectrometer, thus the analysis of all toxins can be accomplished in a single run, increasing sample throughput. The limits of quantification under alkaline conditions met the validation requirements established by the EURLMB for all toxins and matrices, while the remaining conditions failed in some cases. The accuracy of the method and the matrix effects where generally dependent on the mobile phases and the seafood species. The MMS had a moderate positive impact on method accuracy for crude extracts, but it showed poor trueness for seafood species other than mussels when analyzing hydrolyzed extracts. Alkaline conditions with EXS and recovery correction for OA were selected as the most proper conditions in the context of our laboratory. This comparative study can help other laboratories to choose the best conditions for the implementation of LC-MS/MS according to their own necessities.

The Standard Biplot

Biplots are graphical displays of data matrices based on the decomposition of a matrix as the product of two matrices. Elements of these two matrices are used as coordinates for the rows and columns of the data matrix, with an interpretation of the joint presentation that relies on the properties of the scalar product. Because the decomposition is not unique, there are several alternative ways to scale the row and column points of the biplot, which can cause confusion amongst users, especially when software packages are not united in their approach to this issue. We propose a new scaling of the solution, called the standard biplot, which applies equally well to a wide variety of analyses such as correspondence analysis, principal component analysis, log-ratio analysis and the graphical results of a discriminant analysis/MANOVA, in fact to any method based on the singular-value decomposition. The standard biplot also handles data matrices with widely different levels of inherent variance. Two concepts taken from correspondence analysis are important to this idea: the weighting of row and column points, and the contributions made by the points to the solution. In the standard biplot one set of points, usually the rows of the data matrix, optimally represent the positions of the cases or sample units, which are weighted and usually standardized in some way unless the matrix contains values that are comparable in their raw form. The other set of points, usually the columns, is represented in accordance with their contributions to the low-dimensional solution. As for any biplot, the projections of the row points onto vectors defined by the column points approximate the centred and (optionally) standardized data. The method is illustrated with several examples to demonstrate how the standard biplot copes in different situations to give a joint map which needs only one common scale on the principal axes, thus avoiding the problem of enlarging or contracting the scale of one set of points to make the biplot readable. The proposal also solves the problem in correspondence analysis of low-frequency categories that are located on the periphery of the map, giving the false impression that they are important.

Asymptotic robust inferences in the analysis of mean and covariance structures

Structural equation models are widely used in economic, socialand behavioral studies to analyze linear interrelationships amongvariables, some of which may be unobservable or subject to measurementerror. Alternative estimation methods that exploit different distributionalassumptions are now available. The present paper deals with issues ofasymptotic statistical inferences, such as the evaluation of standarderrors of estimates and chi--square goodness--of--fit statistics,in the general context of mean and covariance structures. The emphasisis on drawing correct statistical inferences regardless of thedistribution of the data and the method of estimation employed. A(distribution--free) consistent estimate of $\Gamma$, the matrix ofasymptotic variances of the vector of sample second--order moments,will be used to compute robust standard errors and a robust chi--squaregoodness--of--fit squares. Simple modifications of the usual estimateof $\Gamma$ will also permit correct inferences in the case of multi--stage complex samples. We will also discuss the conditions under which,regardless of the distribution of the data, one can rely on the usual(non--robust) inferential statistics. Finally, a multivariate regressionmodel with errors--in--variables will be used to illustrate, by meansof simulated data, various theoretical aspects of the paper.

Scaling the microrheology of living cells

We report a scaling law that governs both the elastic and frictional properties of a wide variety of living cell types, over a wide range of time scales and under a variety of biological interventions. This scaling identifies these cells as soft glassy materials existing close to a glass transition, and implies that cytoskeletal proteins may regulate cell mechanical properties mainly by modulating the effective noise temperature of the matrix. The practical implications are that the effective noise temperature is an easily quantified measure of the ability of the cytoskeleton to deform, flow, and reorganize.

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.

Influence of sample processing on the analysis of carotenoids in maize

We performed a number of tests with the aim to develop an effective extraction method for the analysis of carotenoid content in maize seed. Mixtures of methanol–ethyl acetate (6:4, v/v) and methanol–tetrahydrofuran (1:1, v/v) were the most effective solvent systems for carotenoid extraction from maize endosperm under the conditions assayed. In addition, we also addressed sample preparation prior to the analysis of carotenoids by liquid chromatography (LC). The LC response of extracted carotenoids and standards in several solvents was evaluated and results were related to the degree of solubility of these pigments. Three key factors were found to be important when selecting a suitable injection solvent: compatibility between the mobile phase and injection solvent, carotenoid polarity and content in the matrix.

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.

On the Rule of Mixtures for Predicting Stress-Softening and Residual Strain Effects in Biological Tissues and Biocompatible Materials

In this work, we use the rule of mixtures to develop an equivalent material model in which the total strain energy density is split into the isotropic part related to the matrix component and the anisotropic energy contribution related to the fiber effects. For the isotropic energy part, we select the amended non-Gaussian strain energy density model, while the energy fiber effects are added by considering the equivalent anisotropic volumetric fraction contribution, as well as the isotropized representation form of the eight-chain energy model that accounts for the material anisotropic effects. Furthermore, our proposed material model uses a phenomenological non-monotonous softening function that predicts stress softening effects and has an energy term, derived from the pseudo-elasticity theory, that accounts for residual strain deformations. The model’s theoretical predictions are compared with experimental data collected from human vaginal tissues, mice skin, poly(glycolide-co-caprolactone) (PGC25 3-0) and polypropylene suture materials and tracheal and brain human tissues. In all cases examined here, our equivalent material model closely follows stress-softening and residual strain effects exhibited by experimental data

Determinació de la ubicació estructural dels ions Yb3+ i Nb3+ en Yb:RTP, Nb:RTP i (Nb,Yb):RTP

Estudi elaborat a partir d’una estada al Stony Brook University al juliol del 2006. El RbTiOPO4 (RTP) monocristal•lí és un material d' òptica no lineal molt rellevant i utilitzat en la tecnologia làser actual, químicament molt estable i amb unes propietats físiques molt destacades, entre elles destaquen els alts coeficients electro-òptics i l'alt llindar de dany òptic que presenta. En els últims anys s’està utilitzant tecnològicament en aplicacions d'òptica no lineal en general i electro-òptiques en particular. En alguns casos ja ha substituït, millorant prestacions, a materials tals com el KTP o el LNB(1). Dopant RTP amb ions lantànids (Ln3+) (2-4), el material es converteix en un material làser auto-doblador de freqüència, combinant les seves propietats no lineals amb les de matriu làser. El RTP genera radiació de segon harmònic (SHG) a partir d’un feix fonamental amb longituds d’ona inferiors a 990 nm, que és el límit que presenta el KTP.La determinació de la ubicació estructural i l’estudi de l'entorn local del ions actius làser és de fonamental importància per a la correcta interpretació de les propietats espectroscòpiques d’aquest material. Mesures de difracció de neutrons sobre mostra de pols cristal•lí mostren que els ions Nb5+ i Ln3+ només substitueixin posicions de Ti4+ (8-9). Estudis molt recents d'EPR (electron paramagnetic resonance) semblen indicar que quan la concentració d'ió Ln3+ es baixa, aquest ió presenta la tendència a substituir l'ió alcalí present a l'estructura (10).Després dels resultats obtinguts en el present treball a partir de la tècnica EXAFS a la instal•lació sincrotò del Brookhaven National Laboratory/State University of New York (Stony Brook) es pot concloure definitivament que els ions Nb s’ubiquen en la posició Ti (1) i que els ions Yb3+ es distribueixen paritariament en les dues posicions del Ti (1 i 2). Aquests resultats aporten una valuosa informació per a la correcta interpretació dels espectres, tant d’absorció com d’emissió, del material i per la avaluació dels paràmetres del seu comportament durant l'acció làser.

Robust Factor Analysis for Compositional Data

Factor analysis as frequent technique for multivariate data inspection is widely used also for compositional data analysis. The usual way is to use a centered logratio (clr)transformation to obtain the random vector y of dimension D. The factor model istheny = Λf + e (1)with the factors f of dimension k & D, the error term e, and the loadings matrix Λ.Using the usual model assumptions (see, e.g., Basilevsky, 1994), the factor analysismodel (1) can be written asCov(y) = ΛΛT + ψ (2)where ψ = Cov(e) has a diagonal form. The diagonal elements of ψ as well as theloadings matrix Λ are estimated from an estimation of Cov(y).Given observed clr transformed data Y as realizations of the random vectory. Outliers or deviations from the idealized model assumptions of factor analysiscan severely effect the parameter estimation. As a way out, robust estimation ofthe covariance matrix of Y will lead to robust estimates of Λ and ψ in (2), seePison et al. (2003). Well known robust covariance estimators with good statisticalproperties, like the MCD or the S-estimators (see, e.g. Maronna et al., 2006), relyon a full-rank data matrix Y which is not the case for clr transformed data (see,e.g., Aitchison, 1986).The isometric logratio (ilr) transformation (Egozcue et al., 2003) solves thissingularity problem. The data matrix Y is transformed to a matrix Z by usingan orthonormal basis of lower dimension. Using the ilr transformed data, a robustcovariance matrix C(Z) can be estimated. The result can be back-transformed tothe clr space byC(Y ) = V C(Z)V Twhere the matrix V with orthonormal columns comes from the relation betweenthe clr and the ilr transformation. Now the parameters in the model (2) can beestimated (Basilevsky, 1994) and the results have a direct interpretation since thelinks to the original variables are still preserved.The above procedure will be applied to data from geochemistry. Our specialinterest is on comparing the results with those of Reimann et al. (2002) for the Kolaproject data

Implementation of zonal control algorithms in adaptive optical systems with sparse control matrices

Miralls deformables més i més grans, amb cada cop més actuadors estan sent utilitzats actualment en aplicacions d'òptica adaptativa. El control dels miralls amb centenars d'actuadors és un tema de gran interès, ja que les tècniques de control clàssiques basades en la seudoinversa de la matriu de control del sistema es tornen massa lentes quan es tracta de matrius de dimensions tan grans. En aquesta tesi doctoral es proposa un mètode per l'acceleració i la paral.lelitzacó dels algoritmes de control d'aquests miralls, a través de l'aplicació d'una tècnica de control basada en la reducció a zero del components més petits de la matriu de control (sparsification), seguida de l'optimització de l'ordenació dels accionadors de comandament atenent d'acord a la forma de la matriu, i finalment de la seva posterior divisió en petits blocs tridiagonals. Aquests blocs són molt més petits i més fàcils de fer servir en els càlculs, el que permet velocitats de càlcul molt superiors per l'eliminació dels components nuls en la matriu de control. A més, aquest enfocament permet la paral.lelització del càlcul, donant una com0onent de velocitat addicional al sistema. Fins i tot sense paral. lelització, s'ha obtingut un augment de gairebé un 40% de la velocitat de convergència dels miralls amb només 37 actuadors, mitjançant la tècnica proposada. Per validar això, s'ha implementat un muntatge experimental nou complet , que inclou un modulador de fase programable per a la generació de turbulència mitjançant pantalles de fase, i s'ha desenvolupat un model complert del bucle de control per investigar el rendiment de l'algorisme proposat. Els resultats, tant en la simulació com experimentalment, mostren l'equivalència total en els valors de desviació després de la compensació dels diferents tipus d'aberracions per als diferents algoritmes utilitzats, encara que el mètode proposat aquí permet una càrrega computacional molt menor. El procediment s'espera que sigui molt exitós quan s'aplica a miralls molt grans.

Estimates of electronic coupling for excess electron transfer in DNA

Electronic coupling Vda is one of the key parameters that determine the rate of charge transfer through DNA. While there have been several computational studies of Vda for hole transfer, estimates of electronic couplings for excess electron transfer (ET) in DNA remain unavailable. In the paper, an efficient strategy is established for calculating the ET matrix elements between base pairs in a π stack. Two approaches are considered. First, we employ the diabatic-state (DS) method in which donor and acceptor are represented with radical anions of the canonical base pairs adenine-thymine (AT) and guanine-cytosine (GC). In this approach, similar values of Vda are obtained with the standard 6-31 G* and extended 6-31++ G* basis sets. Second, the electronic couplings are derived from lowest unoccupied molecular orbitals (LUMOs) of neutral systems by using the generalized Mulliken-Hush or fragment charge methods. Because the radical-anion states of AT and GC are well reproduced by LUMOs of the neutral base pairs calculated without diffuse functions, the estimated values of Vda are in good agreement with the couplings obtained for radical-anion states using the DS method. However, when the calculation of a neutral stack is carried out with diffuse functions, LUMOs of the system exhibit the dipole-bound character and cannot be used for estimating electronic couplings. Our calculations suggest that the ET matrix elements Vda for models containing intrastrand thymine and cytosine bases are essentially larger than the couplings in complexes with interstrand pyrimidine bases. The matrix elements for excess electron transfer are found to be considerably smaller than the corresponding values for hole transfer and to be very responsive to structural changes in a DNA stack