The transformed-stationary approach: a generic and simplified methodology for non-stationary extreme value analysis

Statistical approaches to study extreme events require, by definition, long time series of data. In many scientific disciplines, these series are often subject to variations at different temporal scales that affect the frequency and intensity of their extremes. Therefore, the assumption of stationarity is violated and alternative methods to conventional stationary extreme value analysis (EVA) must be adopted. Using the example of environmental variables subject to climate change, in this study we introduce the transformed-stationary (TS) methodology for non-stationary EVA. This approach consists of (i) transforming a non-stationary time series into a stationary one, to which the stationary EVA theory can be applied, and (ii) reverse transforming the result into a non-stationary extreme value distribution. As a transformation, we propose and discuss a simple time-varying normalization of the signal and show that it enables a comprehensive formulation of non-stationary generalized extreme value (GEV) and generalized Pareto distribution (GPD) models with a constant shape parameter. A validation of the methodology is carried out on time series of significant wave height, residual water level, and river discharge, which show varying degrees of long-term and seasonal variability. The results from the proposed approach are comparable with the results from (a) a stationary EVA on quasi-stationary slices of non-stationary series and (b) the established method for non-stationary EVA. However, the proposed technique comes with advantages in both cases. For example, in contrast to (a), the proposed technique uses the whole time horizon of the series for the estimation of the extremes, allowing for a more accurate estimation of large return levels. Furthermore, with respect to (b), it decouples the detection of non-stationary patterns from the fitting of the extreme value distribution. As a result, the steps of the analysis are simplified and intermediate diagnostics are possible. In particular, the transformation can be carried out by means of simple statistical techniques such as low-pass filters based on the running mean and the standard deviation, and the fitting procedure is a stationary one with a few degrees of freedom and is easy to implement and control. An open-source MAT-LAB toolbox has been developed to cover this methodology, which is available at https://github.com/menta78/tsEva/(Mentaschi et al., 2016).

Multiple solutions and numerical analysis to the dynamic and stationary models coupling a delayed energy balance model involving latent heat and discontinuous albedo with a deep ocean

We study a climatologically important interaction of two of the main components of the geophysical system by adding an energy balance model for the averaged atmospheric temperature as dynamic boundary condition to a diagnostic ocean model having an additional spatial dimension. In this work, we give deeper insight than previous papers in the literature, mainly with respect to the 1990 pioneering model by Watts and Morantine. We are taking into consideration the latent heat for the two phase ocean as well as a possible delayed term. Non-uniqueness for the initial boundary value problem, uniqueness under a non-degeneracy condition and the existence of multiple stationary solutions are proved here. These multiplicity results suggest that an S-shaped bifurcation diagram should be expected to occur in this class of models generalizing previous energy balance models. The numerical method applied to the model is based on a finite volume scheme with nonlinear weighted essentially non-oscillatory reconstruction and Runge–Kutta total variation diminishing for time integration.

Identifying stationary series in panels: A Monte Carlo evaluation of sequential panel selection methods

Sequential panel selection methods (spsms — procedures that sequentially use conventional panel unit root tests to identify I(0)I(0) time series in panels) are increasingly used in the empirical literature. We check the reliability of spsms by using Monte Carlo simulations based on generating directly the individual asymptotic pp values to be combined into the panel unit root tests, in this way isolating the classification abilities of the procedures from the small sample properties of the underlying univariate unit root tests. The simulations consider both independent and cross-dependent individual test statistics. Results suggest that spsms may offer advantages over time series tests only under special conditions.

Direct numerical simulation of statistically stationary and homogeneous shear turbulence and its relation to other shear flows

Statistically stationary and homogeneous shear turbulence (SS-HST) is investigated by means of a new direct numerical simulation code, spectral in the two horizontal directions and compact-finite-differences in the direction of the shear. No remeshing is used to impose the shear-periodic boundary condition. The influence of the geometry of the computational box is explored. Since HST has no characteristic outer length scale and tends to fill the computational domain, long-term simulations of HST are “minimal” in the sense of containing on average only a few large-scale structures. It is found that the main limit is the spanwise box width, Lz, which sets the length and velocity scales of the turbulence, and that the two other box dimensions should be sufficiently large (Lx ≳ 2Lz, Ly ≳ Lz) to prevent other directions to be constrained as well. It is also found that very long boxes, Lx ≳ 2Ly, couple with the passing period of the shear-periodic boundary condition, and develop strong unphysical linearized bursts. Within those limits, the flow shows interesting similarities and differences with other shear flows, and in particular with the logarithmic layer of wall-bounded turbulence. They are explored in some detail. They include a self-sustaining process for large-scale streaks and quasi-periodic bursting. The bursting time scale is approximately universal, ∼20S−1, and the availability of two different bursting systems allows the growth of the bursts to be related with some confidence to the shearing of initially isotropic turbulence. It is concluded that SS-HST, conducted within the proper computational parameters, is a very promising system to study shear turbulence in general.

PROLINE-BASED CHIRAL STATIONARY PHASES: INSIGHTS INTO THE MECHANISM OF CHIRAL SELECTIVITY

Proline (Pro) is a unique amino acid that has been examined previously as a potential chiral selector for high-performance liquid chromatography. In recent years, a new class of promising Pro based enantioselective stationary phases has been studied and the longer peptides were found to be competitive with commercial chiral stationary phases (CSPs). Here, we aim to perform a comprehensive examination of a t-butoxycarbonyl- (t-Boc-) terminated monoproline selector. This selector was grafted through an amide linkage to an aminopropyl siloxane-terminated Si (111) wafer and to a silicon atomic force microscopy tip. To ensure a flat, homogeneous overlayer of selectors suitable for force spectrometric measurements, the prepared surfaces were characterized using XPS, AFM and contact angle measurements. Chemical force spectrometry (CFS) has been used to examine the chiral discrimination in our monoproline CSP by measuring the interaction forces between two D- or L-monoproline monolayers in water and in the presence of a series of amino acids in solution to explore the degree to which binding of amino acids impacts self-selectivity. Chemical force titration (CFT) has been used to observe the influence of variations in pH on the binding interaction of proline modified chiral surfaces. Here we aim to explore the connection between side-chain hydrophobicity and differences in the nature of the binding between different ionic forms of amino acids and the t-Boc-Pro interface, and thereby to gain insight into the mechanism of chiral selectivity. The CFS results show several trends for different proline selector/amino acid combinations and indicate that the binding characteristics of amino acid to the proline surface is strongly dependent on the amino acid side chain where hydrophilic side chain amino acids exhibit a selectivity opposite to that seen for those with hydrophobic side chains. The CFT studies also provide valuable insights into interactions between the proline selector and the amino acids under a wide range of pH conditions, indicating that protonated amine groups of alanine and serine are closely involved in the binding mechanism to proline surfaces. On the other hand, the presence of the second carboxylic group in aspartic acid plays an important role while interacting with proline.

Analysis of Non-Stationary Flows Using Eulerian and Lagrangian Frameworks

Recent developments have made researchers to reconsider Lagrangian measurement techniques as an alternative to their Eulerian counterpart when investigating non-stationary flows. This thesis advances the state-of-the-art of Lagrangian measurement techniques by pursuing three different objectives: (i) developing new Lagrangian measurement techniques for difficult-to-measure, in situ flow environments; (ii) developing new post-processing strategies designed for unstructured Lagrangian data, as well as providing guidelines towards their use; and (iii) presenting the advantages that the Lagrangian framework has over their Eulerian counterpart in various non-stationary flow problems. Towards the first objective, a large-scale particle tracking velocimetry apparatus is designed for atmospheric surface layer measurements. Towards the second objective, two techniques, one for identifying Lagrangian Coherent Structures (LCS) and the other for characterizing entrainment directly from unstructured Lagrangian data, are developed. Finally, towards the third objective, the advantages of Lagrangian-based measurements are showcased in two unsteady flow problems: the atmospheric surface layer, and entrainment in a non-stationary turbulent flow. Through developing new experimental and post-processing strategies for Lagrangian data, and through showcasing the advantages of Lagrangian data in various non-stationary flows, the thesis works to help investigators to more easily adopt Lagrangian-based measurement techniques.

An application of two techniques for the analysis of short, multivariate non-stationary time-series of Mauritanian trawl survey data

Min/max autocorrelation factor analysis (MAFA) and dynamic factor analysis (DFA) are complementary techniques for analysing short (> 15-25 y), non-stationary, multivariate data sets. We illustrate the two techniques using catch rate (cpue) time-series (1982-2001) for 17 species caught during trawl surveys off Mauritania, with the NAO index, an upwelling index, sea surface temperature, and an index of fishing effort as explanatory variables. Both techniques gave coherent results, the most important common trend being a decrease in cpue during the latter half of the time-series, and the next important being an increase during the first half. A DFA model with SST and UPW as explanatory variables and two common trends gave good fits to most of the cpue time-series. (c) 2004 International Council for the Exploration of the Sea. Published by Elsevier Ltd. All rights reserved.

Estimation of the Traffic Intensity in a Piecewise-stationary Mt/Gt/1 Queue with Probing

We use a probing strategy to estimate the time dependent traffic intensity in an Mt/Gt/1 queue, where the arrival rate and the general service-time distribution change from one time interval to another, and derive statistical properties of the proposed estimator. We present a method to detect a switch from a stationary interval to another using a sequence of probes to improve the estimation. At the end, we compare our results with two estimators proposed in the literature for the M/G/1 queue.

Frequency domain analysis of stationary time series

This thesis provides a necessary and sufficient condition for asymptotic efficiency of a nonparametric estimator of the generalised autocovariance function of a Gaussian stationary random process. The generalised autocovariance function is the inverse Fourier transform of a power transformation of the spectral density, and encompasses the traditional and inverse autocovariance functions. Its nonparametric estimator is based on the inverse discrete Fourier transform of the same power transformation of the pooled periodogram. The general result is then applied to the class of Gaussian stationary ARMA processes and its implications are discussed. We illustrate that for a class of contrast functionals and spectral densities, the minimum contrast estimator of the spectral density satisfies a Yule-Walker system of equations in the generalised autocovariance estimator. Selection of the pooling parameter, which characterizes the nonparametric estimator of the generalised autocovariance, controlling its resolution, is addressed by using a multiplicative periodogram bootstrap to estimate the finite-sample distribution of the estimator. A multivariate extension of recently introduced spectral models for univariate time series is considered, and an algorithm for the coefficients of a power transformation of matrix polynomials is derived, which allows to obtain the Wold coefficients from the matrix coefficients characterizing the generalised matrix cepstral models. This algorithm also allows the definition of the matrix variance profile, providing important quantities for vector time series analysis. A nonparametric estimator based on a transformation of the smoothed periodogram is proposed for estimation of the matrix variance profile.

Analysis of the impact of stationary energy storage systems in trolleybus grids using Simulink-based modelling

The voltage profile of the catenary between traction substations (TSSs) is affected by the trolleybus current intake and by its position with respect to the TSSs: the higher the current requested by the bus and the further the bus from the TSSs, the deeper the voltage drop. When the voltage drops below 500V, the trolleybus is forced to decrease its consumption by reducing its input current. This thesis deals with the analysis of the improvements that the installation of an BESS produces in the operation of a particularly loaded FS of the DC trolleybus network of the city of Bologna. The stationary BESS is charged by the TSSs during off-peak times and delivers the stored energy when the catenary is overloaded alleviating the load on the TSSs and reducing the voltage drops. Only IMC buses are considered in the prospect of a future disposal of all internal combustion engine vehicles. These trolleybuses cause deeper voltage drops because they absorb enough current to power their traction motor and recharge the on board battery. The control of the BESS aims to keep the catenary voltage within the admissible voltage range and makes sure that all physical limitations are met. A model of FS Marconi Trento Trieste is implemented in Simulink environment to simulate its daily operation and compare the behavior of the trolleybus network with and without BESS. From the simulation without BESS, the best location of the energy storage system is deduced, and the battery control is tuned. Furthermore, from the knowledge of the load curve and the battery control trans-characteristic, it is formulated a prediction of the voltage distribution at BESS connection point. The prediction is then compared with the simulation results to validate the Simulink model. The BESS allows to decrease the voltage drops along the catenary, the Joule losses and the current delivered by the TSSs, indicating that the BESS can be a solution to improve the operation of the trolleybus network.

The Putative Leishmania Telomerase Rna (leishter) Undergoes Trans-splicing And Contains A Conserved Template Sequence.

Telomerase RNAs (TERs) are highly divergent between species, varying in size and sequence composition. Here, we identify a candidate for the telomerase RNA component of Leishmania genus, which includes species that cause leishmaniasis, a neglected tropical disease. Merging a thorough computational screening combined with RNA-seq evidence, we mapped a non-coding RNA gene localized in a syntenic locus on chromosome 25 of five Leishmania species that shares partial synteny with both Trypanosoma brucei TER locus and a putative TER candidate-containing locus of Crithidia fasciculata. Using target-driven molecular biology approaches, we detected a ∼2,100 nt transcript (LeishTER) that contains a 5' spliced leader (SL) cap, a putative 3' polyA tail and a predicted C/D box snoRNA domain. LeishTER is expressed at similar levels in the logarithmic and stationary growth phases of promastigote forms. A 5'SL capped LeishTER co-immunoprecipitated and co-localized with the telomerase protein component (TERT) in a cell cycle-dependent manner. Prediction of its secondary structure strongly suggests the existence of a bona fide single-stranded template sequence and a conserved C[U/C]GUCA motif-containing helix II, representing the template boundary element. This study paves the way for further investigations on the biogenesis of parasite TERT ribonucleoproteins (RNPs) and its role in parasite telomere biology.

Fases estacionárias monolíticas para separações cromatográficas

Monolithic stationary phases represent a new generation of chromatographic separation media. These phases consist of a continuous separation bed prepared by in situ polymerization or consolidation inside the column tubing. In recent years, their simple preparation procedure, unique properties and excellent performance have attracted quite remarkable attention in liquid chromatography and capillary electrochromatography. This review summarizes the preparation, characterization and applications of monolithic stationary phases. The analytical potential of these columns is demonstrated with separations involving various families of compounds in different separation modes.

Possibilidades e limitações no uso da temperatura em cromatografia líquida de fase reversa

High-temperature liquid chromatography (HTLC) is a technique that presents a series of advantages in liquid phase separations, such as: reduced analysis time, reduced pressure drop, reduced asymmetry factors, modified retentions, controlled selectivities, better efficiencies and improved detectivities, as well as permitting green chromatography. The practical limitations that relate to instrumentation and to stationary phase instability are being resolved and this technique is now ready to be applied for routine determinations.

Cromatografia líquida capilar: estado da arte e aplicações

This review describes the advantages and disadvantages of using capillary liquid chromatography (CLC), which is considered the newest member in the analytical separation science arsenal. Although CLC has tremendous potential for being the next major innovation in separatory analysis, it has not yet obtained great popularity compared to conventional high performance (and ultra-high performance) liquid chromatography. Comparisons are made between these techniques and some of the reasons that CLC has not yet reached its potential will be advanced.

O desafio de analisar solutos básicos por cromatografia líquida em modo reverso: algumas alternativas para melhorar as separações

This review considers some of the difficulties encountered with the analysis of basic solutes using reversed-phase chromatography, such as detrimental interaction with stationary phase silanol groups. Methods of overcoming these problems in reversed-phase separations, by judicious selection of the stationary phase and mobile phase conditions, are discussed. Developments to improve the chemical and thermal stability of stationary phases are also reviewed. It is shown that substantial progress has been made in the manufacturing of stationary phases, enabling their use over a wide variety of experimental conditions. In addition, general measures to significantly extend their lifespan are discussed.