Detecting spatial patterns with the cumulant function. Part I: The theory

In climate studies, detecting spatial patterns that largely deviate from the sample mean still remains a statistical challenge. Although a Principal Component Analysis (PCA), or equivalently a Empirical Orthogonal Functions (EOF) decomposition, is often applied on this purpose, it can only provide meaningful results if the underlying multivariate distribution is Gaussian. Indeed, PCA is based on optimizing second order moments quantities and the covariance matrix can only capture the full dependence structure for multivariate Gaussian vectors. Whenever the application at hand can not satisfy this normality hypothesis (e.g. precipitation data), alternatives and/or improvements to PCA have to be developed and studied. To go beyond this second order statistics constraint that limits the applicability of the PCA, we take advantage of the cumulant function that can produce higher order moments information. This cumulant function, well-known in the statistical literature, allows us to propose a new, simple and fast procedure to identify spatial patterns for non-Gaussian data. Our algorithm consists in maximizing the cumulant function. To illustrate our approach, its implementation for which explicit computations are obtained is performed on three family of of multivariate random vectors. In addition, we show that our algorithm corresponds to selecting the directions along which projected data display the largest spread over the marginal probability density tails.Comment: 9 pages, 3 figure

Detecting spatial patterns with the cumulant function. Part II: An application to El Nino

The spatial coherence of a measured variable (e.g. temperature or pressure) is often studied to determine the regions where this variable varies the most or to find teleconnections, i.e. correlations between specific regions. While usual methods to find spatial patterns, such as Principal Components Analysis (PCA), are constrained by linear symmetries, the dependence of variables such as temperature or pressure at different locations is generally nonlinear. In particular, large deviations from the sample mean are expected to be strongly affected by such nonlinearities. Here we apply a newly developed nonlinear technique (Maxima of Cumulant Function, MCF) for the detection of typical spatial patterns that largely deviate from the mean. In order to test the technique and to introduce the methodology, we focus on the El Nino/Southern Oscillation and its spatial patterns. We find nonsymmetric temperature patterns corresponding to El Nino and La Nina, and we compare the results of MCF with other techniques, such as the symmetric solutions of PCA, and the nonsymmetric solutions of Nonlinear PCA (NLPCA). We found that MCF solutions are more reliable than the NLPCA fits, and can capture mixtures of principal components. Finally, we apply Extreme Value Theory on the temporal variations extracted from our methodology. We find that the tails of the distribution of extreme temperatures during La Nina episodes is bounded, while the tail during El Ninos is less likely to be bounded. This implies that the mean spatial patterns of the two phases are asymmetric, as well as the behaviour of their extremes.Comment: 15 pages, 7 figure

Fast determination of biogenic amines in beverages by a core-shell particle column

A fast and reliable HPLC method for the determination of 11 biogenic amines in beverages has been performed. After pre-column derivatization with dansyl-chloride a Kinetex C18 core–shell particle column (100 mm × 4.6 mm, 2.6 μm particle size) has been employed and the biogenic amines were identified and quantified in a total run time of 13 min with ultraviolet (UV) or fluorescence detection (FLD). Chromatographic conditions such as column temperature (kept at 50 °C), gradient elution and flow rate have been optimized and the method has been tested on red wine and fruit nectar. The proposed method is enhanced in terms of reduced analysis time and eluent consumption with respect of classical HPLC method as to be comparable to UHPLC methods. Green and cost-effective, this method can be used as a quality-control tool for routine quantitative analysis of biogenic amines in beverages for the average laboratory

Chemometric evaluation of biogenic amines in commercial fruit juices

The profile and level of 11 biogenic amines were evaluated in commercial fruit juices (apple, grapefruit, orange and pineapple) and fruit nectars (apricot, peach and pear) by HPLC/FD after dansyl chloride derivatization. The biogenic amine most present in nectars is cadaverine, followed by putrescine, spermidine and spermine. Fruit juices showed a wider variability in biogenic amines profile and level, with the highest total content in orange juices. The application of chemometric tools as hierarchical cluster analysis and principal component analysis on the biogenic amine profiles of the juice samples succeeded in grouping juices on the basis of the fruit of origin. A Mathematical model with high predictive ability for fruit juices classification was obtained by linear discriminant analysis: orange (100 %), pineapple (100 %), grapefruit (80 %) and apple (70 %). This study represents the first description of biogenic amines content in these beverages. These compounds are well-known important quality parameters and demonstrated to have also a characteristic profile depending on the fruit of origin

O Conhecimento (Da'at) de Iahweh como Justificação em Is 52,13-53,12

O objeto da nossa dissertação é aprofundar o valor da teologia da Justificação presente em Is 52,13-53,12. Este texto é o quarto dum conjunto de quatro poemas que relatam a atuação duma personagem misteriosa, conhecida como o Servo de Iahweh. O ponto de partida será uma análise das relações que o conjunto dos cânticos mantém com o contexto deuteroisaiano. Em seguida, focalizamo-nos no tema da missão, leit motive destes textos, reservando desde logo uma especial atenção ao quarto poema. Estudaremos o papel do sofrimento vigário e de como ele concorre para a realização da Expiação, Intercessão e Justificação, numa lógica de Stellvertretung ou Representação. Segundo o verso 53,11, o desfecho final da missão do Servo é a «justificação dos muitos» (Seḏeq). Ela aparece no texto interligada com outra categoria muito importante do pensamento bíblico: o conhecimento (Da’at). Apresentaremos toda a problemática relativa ao arranjo sintático e gramatical deste verso, considerado enigmático e de difícil compreensão por muitos estudiosos. Em seguida, desenvolveremos o significado que Da’at adquire na literatura profética juntamente com outras virtudes da Aliança como o amor (Hesed) e a fidelidade (‘Emet). Descobriremos como a atuação do Servo descrita nestes termos tem um valor fortemente soteriológico que confere nova luz aos mistérios do sofrimento, do pecado e da morte.The object of the present dissertation is to extend the value of the justification’s theology of Is 52, 13-53,12. It is the fourth text of a group of four poems that narrate the behavior of a mysterious character known as the Servant of Iahweh. We begin with an analysis of the relationships that this set of songs has with the deutero-Isaian context. Up next, we focus on the mission theme, which is the leit motive of these texts, giving special attention to the fourth poem. We will study the role of the vicarious suffering and how it concurs to the Atonement, Intercession and Justification, from a Stellvertretung point of view. According to the verse 53,11, the final outcome of the Servant’s mission is the «justification of many» (Sedeq). This theme appears in the text interconnected with another, very important, category of the biblical thought: knowledge (Da’at). We present all the problematic concerning the syntactical and grammatical arrangement of this verse, considered to be cryptic and difficult to comprehend by many scholars. Next, we will develop the significance that Da’at acquires in the prophetical literature, alongside with other virtues of the Covenant, such as love (Hesed) and fidelity (‘Emet). We will discover how the actuation of the Servant described with these terms has an highly soteriological value, which sheds a new light to the mysteries of suffering, sin and death

Non-reversible Gaussian processes for identifying latent dynamical structure in neural data

A common goal in the analysis of neural data is to compress large population recordings into sets of interpretable, low-dimensional latent trajectories. This problem can be approached using Gaussian process (GP)-based methods which provide uncertainty quantification and principled model selection. However, standard GP priors do not distinguish between underlying dynamical processes and other forms of temporal autocorrelation. Here, we propose a new family of “dynamical” priors over trajectories, in the form of GP covariance functions that express a property shared by most dynamical systems: temporal non-reversibility. Non-reversibility is a universal signature of autonomous dynamical systems whose state trajectories follow consistent flow fields, such that any observed trajectory could not occur in reverse. Our new multi-output GP kernels can be used as drop-in replacements for standard kernels in multivariate regression, but also in latent variable models such as Gaussian process factor analysis (GPFA). We therefore introduce GPFADS (Gaussian Process Factor Analysis with Dynamical Structure), which models single-trial neural population activity using low-dimensional, non-reversible latent processes. Unlike previously proposed non-reversible multi-output kernels, ours admits a Kronecker factorization enabling fast and memory-efficient learning and inference. We apply GPFADS to synthetic data and show that it correctly recovers ground truth phase portraits. GPFADS also provides a probabilistic generalization of jPCA, a method originally developed for identifying latent rotational dynamics in neural data. When applied to monkey M1 neural recordings, GPFADS discovers latent trajectories with strong dynamical structure in the form of rotations

Cloning, molecular characterization and tissue exPression of an octoPamine/tyramine recePtor from sPotted wing drosoPhila (DROSOPHILA SUZUKII)

Spotted wing Drosophila (Drosophila suzukii) is a polyphagous pest arrived in Europe in 2009 able to infest a growing number of fruit and vine species, causing considerable economic damage. D. suzukii grows very rapidly (seven to fifteen generations per year) and shows a remarkable ability to adapt to climatic conditions and to new host plants. These characteristics make its populations particularly difficult to control. Octopamine (OA) and tyramine (TA) biogenic amines are present in traces in vertebrates, while in invertebrates they act as substitutes for adrenaline and noradrenaline. Indeed, these amines regulate numerous physiological processes in insects. They exert their effects by binding to specific receptor proteins that belong to the superfamily of G-protein coupled receptors (GPCRs). In this work, we have isolated complementary DNA (cDNA) coding for an amine receptor from Drosophila suzukii (DsTyr). The cloned cDNA is about 1.8kb long and encodes for a 601 amino acids protein. This polypeptide presents the classical seven transmembrane domains as revealed by hydropathic profile analysis. BLAST analysis of the sequence shows a high identity (>98%) to the octopamine/tyramine receptor from Drosophila melanogaster. DsTyr1 deduced sequence will be compared to the amino acid sequence of octopamine/tyramine receptors from other insects. Furthermore, the various receptor sequences will be characterized by phylogenetic analysis. The expression level of the receptor will be studied by qRT-PCR analysis in different parts of D. suzukii male and female body (head, thorax and abdomen). With this work, we present a first structural and functional description of an octopamine/tyramine receptor from Drosophila suzukii