Solution-processed field-effect transistors are strategic building blocks when considering low-cost sustainable flexible electronics. Nevertheless, some challenges (e.g., processing temperature, reliability, reproducibility in large areas, and cost effectiveness) are requirements that must be surpassed in order to achieve high-performance transistors. The present work reports electrolyte-gated transistors using as channel layer gallium-indium-zinc-oxide nanoparticles produced by solvothermal synthesis combined with a solid-state electrolyte based on aqueous dispersions of vinyl acetate stabilized with cellulose derivatives, acrylic acid ester in styrene and lithium perchlorate. The devices fabricated using this approach display a ION/IOFF up to 1 × 10(6), threshold voltage (VTh) of 0.3-1.9 V, and mobility up to 1 cm(2)/(V s), as a function of gallium-indium-zinc-oxide ink formulation and two different annealing temperatures. These results validates the usage of electrolyte-gated transistors as a viable and promising alternative for nanoparticle based semiconductor devices as the electrolyte improves the interface and promotes a more efficient step coverage of the channel layer, reducing the operating voltage when compared with conventional dielectrics gating. Moreover, it is shown that by controlling the applied gate potential, the operation mechanism of the electrolyte-gated transistors can be modified from electric double layer to electrochemical doping.

Nowadays fiber reinforced polymer (FRP) composites play an important role in the strengthening of structures. Different methods can be used to apply these materials: the externally bonded reinforcement (EBR), and the near surface mounted (NSM) using strips and NSM rods. There are only a few studies comparing these methods or presenting an efficient model to simulate these strengthening techniques. This study looks mainly at the analysis of the interface between FRP-to-parent material bonded joints. The paper examines, through a new discrete model based on axial and shear springs, the performance of FRP-to-parent material bonded joints for EBR or NSM techniques using strips or composite rods. In order to implement the model a routine in MATLAB was developed and several bond–slip curves were assumed. The results revealed that load–slip curves or bond stresses, strains or slippages along the bonded length obtained from several bond–slip curves are similar to the analytical and other numerical solutions found in literature. In what concerns the adhesion between two different materials, and assuming the same bond characteristics for the three fiber strengthening techniques, the NSM system using FRP strips had the highest maximum load transmitted to the FRP strip combined with the lowest effective bond length. The results obtained from the proposed model were also very accurate with that obtained from an analytical solution found in literature that simulates the debonding phenomenon of FRP-to-concrete interfaces between to adjacent cracks.

A demanda de energia, faz com que o homem esteja sempre a procura de novas soluções para a sua produção. Uma opção é a energia eólica, por se tratar de uma energia limpa, renovável e inesgotável. Para se evitar a ocupação das terras férteis, é natural a busca de soluções no mar. Portanto, neste trabalho é estudado o comportamento estrutural dinâmico de uma torre treliçada em concreto armado pós-tensionado por tirantes externos idealizada para uso offshore com a finalidade de suporte para turbinas eólicas de eixo horizontal. A torre está sujeita às ações gravitacionais, aerodinâmicas e hidrodinâmicas. Para considerar estas ações desenvolveu-se um código computacional específico usando a linguagem MATLAB. É proposto um modelo simplificado para análise bi-dimensional, utilizando-se elementos de pórtico plano com a finalidade de contornar as dificuldades de uma análise tridimensional. Embora específico para este tipo de torre, o codigo permite variar geometrias, carregamentos e alterações do nível do mar. Nas cargas aerodinâmicas élevado em conta o espectro de Von Karman. As cargas hidrodinâmicas são avaliadas pela equação de Morison. As cargas nodais equivalentes são determinadas por integração ao longo do elemento estrutural de acordo com o proposto por Souza. Os tirantes pós-tensionados são monitorados para não sofrerem esforços de compressão. A análise é realizada no domínio do tempo utilizando-se o algoritmo de integração de Newmark.. Através dos procedimentos adotados foi possível obter resultados para as freqüências, deslocamentose esforços, que se mostraram coerentes com os obtidos por modelos tri dimensionais mais complexos. O código desenvolvido permitiu a análise de forma simples, eficiente e confiável de torres treliçadas de concreto armado.

Este trabalho apresenta o desenvolvimento de um software para análise de torres treliçadas em concreto armado, pós-tensionada por tirantes externos, com a finalidade de suporte para turbinas eólicas de eixo horizontal, em ambiente offshore. A torre está sujeita às ações gravitacionais, aerodinâmicas, hidrodinâmicas. Desenvolveu-se um código computacional, em linguagem MATLAB, específico para este tipo de torre. As dificuldades de uma análise tridimensional mais complexa foram reduzidas propondo-se um modelo simplificado bi-dimensional utilizando-se elementos de pórtico plano. As cargas de vento são variadas segundo o espectro de von Karman. Para as ondas marítimas e correntes são implementados o espectro de Pierson-Moskowitz e o de JONSWAP. As cargas hidrodinâmicas são avaliadas pela equação de Morison. Estas cargas são integradas ao longo dos elementos estruturais e transformadas em cargas nodais equivalentes, de acordo com o proposto por Souza. A análise é realizada no domínio do tempo com algoritmo de Newmark. Este software, por ser específico para este tipo de torre, possui facilidades na introdução de dados e na modelagem da estrutura. Com estas estratégias o modelo apresentou bons resultados para a avaliação de cargas, cálculo de freqüências naturais, resposta de deslocamentos, esforços e reações.

The Pareto distribution is a well known and important model in Statistics. It has been used to study large incomes, city population size, size of losses, stock price fluctuations, number of citations received by papers and other similar phenomena. In this work we compare the finite sample performance of several estimation methods, namely the Moment, Maximum Likelihood and Quantile Regression methods. The comparison will be made through a Monte-Carlo simulation study.The Pareto distribution is a well known and important model in Statistics. It has been used to study large incomes, city population size, size of losses, stock price fluctuations, number of citations received by papers and other similar phenomena. In this work we compare the finite sample performance of several estimation methods, namely the Moment, Maximum Likelihood and Quantile Regression methods. The comparison will be made through a Monte-Carlo simulation study.

In Statistics of Extremes, the tail shape second order parameter is a relevant parameter whenever we want to improve the estimation of first order parameters. We shall consider two semi-parametric estimators of the shape second order parameter, parameterized with a tuning parameter. We provide a Monte Carlo comparative simulation study of several algorithms for the choice of such tuning parameter and for an adaptive estimation of the shape second order parameter.In Statistics of Extremes, the tail shape second order parameter is a relevant parameter whenever we want to improve the estimation of first order parameters. We shall consider two semi-parametric estimators of the shape second order parameter, parameterized with a tuning parameter. We provide a Monte Carlo comparative simulation study of several algorithms for the choice of such tuning parameter and for an adaptive estimation of the shape second order parameter.

In this article, we revisit Feuerverger and Halls maximum likelihood estimation of the extreme value index. Based on those estimators we propose new estimators that have the smallest possible asymptotic variance, equal to the asymptotic variance of the Hill estimator. The full asymptotic distributional properties of the estimators are derived under a general third-order framework for heavy tails. Applications to a real data set and to simulated data are also presented.In this article, we revisit Feuerverger and Halls maximum likelihood estimation of the extreme value index. Based on those estimators we propose new estimators that have the smallest possible asymptotic variance, equal to the asymptotic variance of the Hill estimator. The full asymptotic distributional properties of the estimators are derived under a general third-order framework for heavy tails. Applications to a real data set and to simulated data are also presented.

In extreme value theory, the shape second-order parameter is a quite relevant parameter related to the speed of convergence of maximum values, linearly normalized, towards its limit law. The adequate estimation of this parameter is vital for improving the estimation of the extreme value index, the primary parameter in statistics of extremes. In this article, we consider a recent class of semi-parametric estimators of the shape second-order parameter for heavy right-tailed models. These estimators, based on the largest order statistics, depend on a real tuning parameter, which makes them highly flexible and possibly unbiased for several underlying models. In this article, we are interested in the adaptive choice of such tuning parameter and the number of top order statistics used in the estimation procedure. The performance of the methodology for the adaptive choice of parameters is evaluated through a Monte Carlo simulation study.In extreme value theory, the shape second-order parameter is a quite relevant parameter related to the speed of convergence of maximum values, linearly normalized, towards its limit law. The adequate estimation of this parameter is vital for improving the estimation of the extreme value index, the primary parameter in statistics of extremes. In this article, we consider a recent class of semi-parametric estimators of the shape second-order parameter for heavy right-tailed models. These estimators, based on the largest order statistics, depend on a real tuning parameter, which makes them highly flexible and possibly unbiased for several underlying models. In this article, we are interested in the adaptive choice of such tuning parameter and the number of top order statistics used in the estimation procedure. The performance of the methodology for the adaptive choice of parameters is evaluated through a Monte Carlo simulation study.

In this paper we review the properties of the difference-sign randomness test. First we analyse the exact andasymptotic distribution of the test statistic and provide a table with values for the exact distribution function, for samples ofsize n ≤ 32. Then, we also present several moments of the statistic test, under the null hypothesis of randomness and underthe hypothesis of the existence of a linear trend. Finally, we present an illustration of the test difference-sign to a real data set.In this paper we review the properties of the difference-sign randomness test. First we analyse the exact andasymptotic distribution of the test statistic and provide a table with values for the exact distribution function, for samples ofsize n ≤ 32. Then, we also present several moments of the statistic test, under the null hypothesis of randomness and underthe hypothesis of the existence of a linear trend. Finally, we present an illustration of the test difference-sign to a real data set.

The number of floods in the city of Venice has increased substantially in the last decades and can be explained bythe sea level rise and land subsidence. Using Statistics of Extremes we shall model the extreme behaviour of the sea level inVenice and quantify risk through the estimation of important parameters such as return periods of high levels.The number of floods in the city of Venice has increased substantially in the last decades and can be explained bythe sea level rise and land subsidence. Using Statistics of Extremes we shall model the extreme behaviour of the sea level inVenice and quantify risk through the estimation of important parameters such as return periods of high levels.

In this paper we consider the semi-parametric estimation of extreme quantiles of a right heavy-tail model. We propose a new Probability Weighted Moment estimator for extreme quantiles, which is obtained from the estimators of the shape and scale parameters of the tail. Under a second-order regular variation condition on the tail, of the underlying distribution function, we deduce the non degenerate asymptotic behaviour of the estimators under study and present an asymptotic comparison at their optimal levels. In addition, the performance of the estimators is illustrated through an application to real data.In this paper we consider the semi-parametric estimation of extreme quantiles of a right heavy-tail model. We propose a new Probability Weighted Moment estimator for extreme quantiles, which is obtained from the estimators of the shape and scale parameters of the tail. Under a second-order regular variation condition on the tail, of the underlying distribution function, we deduce the non degenerate asymptotic behaviour of the estimators under study and present an asymptotic comparison at their optimal levels. In addition, the performance of the estimators is illustrated through an application to real data.