Irrigation canals in a semi-arid agricultural landscape surrounded by wetlands: Their role as a habitat for birds during the breeding season

Traditional water supply systems in semi-arid agrarian ecosystems, mainly irrigation canals, contribute to the diversity of the landscape and influence the composition of species. To evaluate their effect on bird communities in the breeding season, we selected a rural area in southeastern Spain, where an intricate and extensive network of irrigation canals and cultivated areas is located between two wetlands declared as Natural Parks. Birds were counted at representative points distributed throughout the canal network at which we recorded several variables related to the physical features, the vertical and horizontal structure of associated vegetation, reed development (Phragmites australis) and land use in the neighboring areas. We detected 37 bird species, most of which were also breeding in the wetlands nearby. We used Hierarchical Partitioning analyses to identify the variables most strongly related to the probability of the presence of selected species and species richness. Vegetation cover and height close to the canals, together with reed development, were the most important types of variables explaining species presence and richness. We found that current management practices for reeds in canals are not well-suited for biodiversity conservation. We therefore propose alternatives that could be implemented in the area in cooperation with stakeholders.

El traductor e intérprete emprendedor: análisis de la supervivencia de las empresas y los empresarios autónomos

This study presents an empirical analysis of the determinants of firm and self-employed survival in the Spanish translation sector. In the midst of a global downturn firm and self-employed survival is a key factor for the progress of the economies and for a better and more stable future. The study presents, first of all, a review of the literature on translation, interpreting, career opportunities, and entrepreneurship, and firm survival. The following empirical analysis explores the combination of variables of human capital, contingency and economic investment that potentially drive translation and interpreting firms or self-employed entrepreneurs to survive. The study performs a comparative qualitative analysis with a fs/QCA methodology identifying nine combination of causes that lead to the outcome. The results contribute towards a better understanding of entrepreneur translators’ lifespan as they provide an empirical outlook on the different causal paths that predict the survival of those translation and interpreting firms or self-employed entrepreneurs. The last part concludes with the most relevant findings of this research study. With little literature on the topic of firm survival in the translation and interpreting sector the paper aims to fill this gap and make a valuable contribution to the current literature on translation-firm creation and firm and self-employed survival.

A Finite Element Numerical Algorithm for Modelling and Data Fitting in Complex Systems

Numerical modelling methodologies are important by their application to engineering and scientific problems, because there are processes where analytical mathematical expressions cannot be obtained to model them. When the only available information is a set of experimental values for the variables that determine the state of the system, the modelling problem is equivalent to determining the hyper-surface that best fits the data. This paper presents a methodology based on the Galerkin formulation of the finite elements method to obtain representations of relationships that are defined a priori, between a set of variables: y = z(x1, x2,...., xd). These representations are generated from the values of the variables in the experimental data. The approximation, piecewise, is an element of a Sobolev space and has derivatives defined in a general sense into this space. The using of this approach results in the need of inverting a linear system with a structure that allows a fast solver algorithm. The algorithm can be used in a variety of fields, being a multidisciplinary tool. The validity of the methodology is studied considering two real applications: a problem in hydrodynamics and a problem of engineering related to fluids, heat and transport in an energy generation plant. Also a test of the predictive capacity of the methodology is performed using a cross-validation method.

Developing an underlying inflation gauge for China. Bruegel Working Paper 2014/11, 9 October 2014

This paper develops a new underlying inflation gauge (UIG) for China which differentiates between trend and noise, is available daily and uses a broad set of variables that potentially influence inflation. Its construction follows the works at other major central banks, adopts the methodology of a dynamic factor model that extracts the lower frequency components as developed by Forni et al (2000) and draws on the experience of the People’s Bank of China in modelling inflation.

Electoral Volatility, Political Sophistication, Trust and Efficacy

In this article we investigate voter volatility and analyze the causes and motives of switching vote intentions. We test two main sets of variables linked to volatility in literature; political sophistication and ‘political (dis)satisfaction’. Results show that voters with low levels of political efficacy tend to switch more often, both within a campaign and between elections. In the analysis we differentiate between campaign volatility and inter-election volatility and by doing so show that the dynamics of a campaign have a profound impact on volatility. The campaign period is when the lowly sophisticated switch their vote intention. Those with higher levels of interest in politics have switched their intention before the campaign has started. The data for this analysis are from the three wave PartiRep Belgian Election Study (2009).

El "Análisis de Correspondencias Múltiples" como herramienta metodológica de síntesis teórica y empírica : Su aporte al estudio del locus universitario privado argentino (1955-1983)

El Análisis de Correspondencias Múltiples (ACM), recurso metodológico utilizado por Bourdieu y su equipo en un nivel avanzado de síntesis teórico-empírica, constituye una herramienta fundamental para la construcción analítica de espacios relacionales. Permite posicionar relacionalmente unidades de análisis en función de un conjunto determinado de variables y plasmar la multiplicidad resultante tanto gráfica como analíticamente. Comenzando por una reflexión general sobre las potencialidades de la herramienta, este artículo analiza la configuración del espacio universitario privado en Argentina (1955-1983) a partir del ACM, que permitió determinar las relaciones de homología y principios de diferenciación existentes entre las instituciones que lo componen.

Safety study : risk factors associated with weather-related general aviation accidents /

The goal of this National Transportation Safety Board study was to better understand the risk factors associated with accidents that occur in weather conditions characterized by IMC or poor visibility ("weather-related accidents"). The study accomplished this goal using the case control methodology, which compared a group of accident flights to a matching group of nonaccident flights to identify patterns of variables that distinguished the two groups from each other. This methodology expands on previous Safety Board efforts that have typically concentrated on summaries of accident cases. For this study, Safety Board air safety investigators (ASI) collected data from 72 GA accidents that occurred between August 2003 and April 2004.

The transform likelihood ratio method for rare event simulation with heavy tails

We present a novel method, called the transform likelihood ratio (TLR) method, for estimation of rare event probabilities with heavy-tailed distributions. Via a simple transformation ( change of variables) technique the TLR method reduces the original rare event probability estimation with heavy tail distributions to an equivalent one with light tail distributions. Once this transformation has been established we estimate the rare event probability via importance sampling, using the classical exponential change of measure or the standard likelihood ratio change of measure. In the latter case the importance sampling distribution is chosen from the same parametric family as the transformed distribution. We estimate the optimal parameter vector of the importance sampling distribution using the cross-entropy method. We prove the polynomial complexity of the TLR method for certain heavy-tailed models and demonstrate numerically its high efficiency for various heavy-tailed models previously thought to be intractable. We also show that the TLR method can be viewed as a universal tool in the sense that not only it provides a unified view for heavy-tailed simulation but also can be efficiently used in simulation with light-tailed distributions. We present extensive simulation results which support the efficiency of the TLR method.

Identifying and predicting adolescent smokers' developmental trajectories

Very few studies have defined trajectories of smoking. In the present study, we modeled growth in adolescent smoking and empirically identified prototypical trajectories. We conceptualized escalation of smoking as a growth process and modeled rates of change and heterogeneity of these patterns using latent growth mixture modeling. The analysis identified six trajectories with low ambiguity about group membership (early rapid escalators, late rapid escalators, late moderate escalators, late slow escalators-smokers, stable puffers, and late slow escalators-puffers). A trajectory of quitters was not identified. We also examined predictors of the smoking trajectories. The predictors were assessed across the adolescent years and included variables related to smoking and other substance use, as well as a range of variables related to sociodemographic factors and mental health. Observed change in the pattern of predictors across age has implications for the mechanism of effect of these variables in relation to smoking trajectories, including predictors that differentiated among daily smokers, variables that may determine the trajectory (e.g., friends smoking), and variables that may result from the trajectory (e.g., marijuana use, less attachment to friends).

Subordinate-manager gender combination and perceived leadership style influence on emotions, self-esteem and organizational commitment

A theoretical model was developed to investigate the relationships among subordinate-manager gender combinations, perceived leadership style, experienced frustration and optimism, organization-based self-esteem and organizational commitment. The model was tested within the context of a probabilistic structural model, a discrete Bayesian network, using cross-sectional data from a global pharmaceutical company. The Bayesian network allowed forward inference to assess the relative influence of gender combination and leadership style on the emotions, self-esteem and commitment consequence variables. Further, diagnostics from backward inference were used to assess the relative influence of variables antecedent to organizational commitment. The results showed that gender combination was independent of leadership style and had a direct impact on subordinates' levels of frustration and optimism. Female manager-female subordinate had the largest probability of optimism, while male manager teamed with a male subordinate had the largest probability of frustration. Furthermore, having a female manager teamed up with a male subordinate resulted in the lowest possibility of frustration. However, the findings show that the gender issue is not simply female managers versus male managers, but is concerned with the interaction of the subordinate-manager gender combination and leadership style in a nonlinear manner. (C) 2003 Elsevier Inc. All rights reserved.

Multiple imputation for body mass index: lessons from the Australian Longitudinal Study on Women's Health

In large epidemiological studies missing data can be a problem, especially if information is sought on a sensitive topic or when a composite measure is calculated from several variables each affected by missing values. Multiple imputation is the method of choice for 'filling in' missing data based on associations among variables. Using an example about body mass index from the Australian Longitudinal Study on Women's Health, we identify a subset of variables that are particularly useful for imputing values for the target variables. Then we illustrate two uses of multiple imputation. The first is to examine and correct for bias when data are not missing completely at random. The second is to impute missing values for an important covariate; in this case omission from the imputation process of variables to be used in the analysis may introduce bias. We conclude with several recommendations for handling issues of missing data. Copyright (C) 2004 John Wiley Sons, Ltd.

First-principles quantum dynamics in interacting Bose gases: I. The positive P representation

The performance of the positive P phase-space representation for exact many- body quantum dynamics is investigated. Gases of interacting bosons are considered, where the full quantum equations to simulate are of a Gross-Pitaevskii form with added Gaussian noise. This method gives tractable simulations of many-body systems because the number of variables scales linearly with the spatial lattice size. An expression for the useful simulation time is obtained, and checked in numerical simulations. The dynamics of first-, second- and third-order spatial correlations are calculated for a uniform interacting 1D Bose gas subjected to a change in scattering length. Propagation of correlations is seen. A comparison is made with other recent methods. The positive P method is particularly well suited to open systems as no conservation laws are hard-wired into the calculation. It also differs from most other recent approaches in that there is no truncation of any kind.

Constructing internationally comparable real income aggregates by combining sparse benchmark data with annual national accounts data: A state-space approach

The importance of availability of comparable real income aggregates and their components to applied economic research is highlighted by the popularity of the Penn World Tables. Any methodology designed to achieve such a task requires the combination of data from several sources. The first is purchasing power parities (PPP) data available from the International Comparisons Project roughly every five years since the 1970s. The second is national level data on a range of variables that explain the behaviour of the ratio of PPP to market exchange rates. The final source of data is the national accounts publications of different countries which include estimates of gross domestic product and various price deflators. In this paper we present a method to construct a consistent panel of comparable real incomes by specifying the problem in state-space form. We present our completed work as well as briefly indicate our work in progress.

Cinderella and the wicked stepmother: How do we perceive step and biological families?

Undergraduate psycholog)' students from stepfamilies (always one step and one biological parent) and biologically intact families (always both biological parents) participated in this study. The goal was to assess perceptions of stepfamilies (N = 106, Nstepfamilies = 44, Nbiological = 62, age range = 17.17 to 28.92 years, M = 19.46 years). One theoretical perspective, the social stigma h)'pothesis, argues that there is a stigma attached to stepfamilies, or that stepfamilies are consistentiy associated with negative stereotypes. In the current study, participants were assessed on a number of variables, including a semantic differential scale, a perceived conflict scale and a perceived general satisfaction scale. It was found that a consistently negative view of stepfamilies was prevalent. Furthermore, the negative stereotypes existed, irrespective of participant family type. Results support the theoretical view that stepfamilies are stereotypically viewed as negative, when compared to biological families.

O IMPACTO DE PERCEPÇÃO DE SUPORTE ORGANIZACIONAL E COMPROMETIMENTO ORGANIZACIONAL AFETIVO SOBRE A INTENÇÃO DE ROTATIVIDADE

O objetivo geral deste estudo foi analisar, interpretar e discutir as relações entre a percepção de suporte organizacional, comprometimento organizacional afetivo e intenção de rotatividade e os efeitos das variáveis: gênero, idade, tempo de trabalho e chefia sobre a intenção de rotatividade. Participaram deste estudo 132 trabalhadores que atuam no estado de São Paulo em organizações públicas e privadas. Como instrumento para a coleta de dados foi utilizado um questionário de autopreenchimento composto por três escalas que mediram as variáveis. A presente pesquisa se propôs a apresentar, interpretar e discutir as relações entre as variáveis, como também, testar as hipóteses referentes ao modelo conceitual proposto, por meio de uma pesquisa de natureza transversal com abordagem quantitativa, cujos dados coletados foram analisados por aplicação de técnicas estatísticas paramétricas (cálculos de estatísticas descritivas: médias, desvio padrão, teste t student, correlações e cálculos de estatísticas multivariadas: analise da regressão múltipla hierárquica). O tratamento e análise dos dados foram realizados pelo software estatístico Statistical Package for Social Science SPSS, versão 19.0 para Windows. Os resultados obtidos demonstraram que percepção de suporte organizacional e o comprometimento organizacional são preditores diretos de intenção de rotatividade. As variáveis: gênero, idade, tempo de trabalho e chefia não apresentaram coeficientes de regressão significantes, portanto não é possível afirmar que são antecedentes de intenção de rotatividade. Os resultados foram discutidos à luz da literatura da área, tendo sido comparados com resultados de outros estudos empíricos.