Observing interactions between children and adolescents and their parents: the effects of anxiety disorder and age

Parental behaviors, most notably overcontrol, lack of warmth and expressed anxiety, have been implicated in models of the development and maintenance of anxiety disorders in children and young people. Theories of normative development have proposed that different parental responses are required to support emotional development in childhood and adolescence, yet age has not typically been taken into account in studies of parenting and anxiety disorders. In order to identify whether associations between anxiety disorder status and parenting differ in children and adolescents, we compared observed behaviors of parents of children (7–10 years) and adolescents (13–16 years) with and without anxiety disorders (n=120), while they undertook a series of mildly anxiety-provoking tasks. Parents of adolescents showed significantly lower levels of expressed anxiety, intrusiveness and warm engagement than parents of children. Furthermore, offspring age moderated the association between anxiety disorder status and parenting behaviors. Specifically, parents of adolescents with anxiety disorders showed higher intrusiveness and lower warm engagement than parents of non-anxious adolescents. A similar relationship between these parenting behaviors and anxiety disorder status was not observed among parents of children. The findings suggest that theoretical accounts of the role of parental behaviors in anxiety disorders in children and adolescents should distinguish between these different developmental periods. Further experimental research to establish causality, however, would be required before committing additional resources to targeting parenting factors within treatment.

Bond graph models of DC-DC converters operating in both CCM and DCM

In this paper, Bond Graphs are employed to develop a novel mathematical model of conventional switched-mode DC-DC converters valid for both continuous and discontinuous conduction modes. A unique causality bond graph model of hybrid models is suggested with the operation of the switch and the diode to be represented by a Modulated Transformer with a binary input and a resistor with fixed conductance causality. The operation of the diode is controlled using an if-then function within the model. The extracted hybrid model is implemented on a Boost and Buck converter with their operations to change from CCM to DCM and to return to CCM. The vector fields of the models show validity in a wide operation area and comparison with the simulation of the converters using PSPICE reveals high accuracy of the proposed model, with the Normalised Root Means Square Error and the Maximum Absolute Error remaining adequately low. The model is also experimentally tested on a Buck topology.

Synapses in digital medium: computational investigations of neural basis of anticipation

Anticipation is an emerging concept that can provide a bridge between the deepest philosophical theories about the nature of life and cognition on one hand and the empirical biological sciences steeped in reductionist and Newtonian conception of causality. Three conceptions of anticipation have been emerging from the literature that may be operationalised in a way leading to a viable empirical programme. The discussion of the research into a novel dynamical concept of anticipating synchronisation lends credence to such a possibility and suggests further links between the three anticipation paradigms. A careful progress mindful to the deep philosophical concerns but also respecting empirical evidence will ultimately lead towards unifying theoretical and empirical biological sciences and may offer progress where reductionist science have been so far faltering.

Carbon trading for phosphorus gain: the balance between rhizosphere carboxylates and arbuscular mycorrhizal symbiosis in plant phosphorus acquisition

Two key plant adaptations for phosphorus (P) acquisition are carboxylate exudation into the rhizosphere and mycorrhizal symbioses. These target different soil P resources, presumably with different plant carbon costs. We examined the effect of inoculation with arbuscular mycorrhizal fungi (AMF) on amount of rhizosphere carboxylates and plant P uptake for 10 species of low-P adapted Kennedia grown for 23 weeks in low-P sand. Inoculation decreased carboxylates in some species (up to 50%), decreased plant dry weight (21%) and increased plant P content (23%). There was a positive logarithmic relationship between plant P content and the amount of rhizosphere citric acid for inoculated and uninoculated plants. Causality was indicated by experiments using sand where little citric acid was lost from the soil solution over 2 h and citric acid at low concentrations desorbed P into the soil solution. Senesced leaf P concentration was often low and P-resorption efficiencies reached >90%. In conclusion, we propose that mycorrhizally mediated resource partitioning occurred because inoculation reduced rhizosphere carboxylates, but increased plant P uptake. Hence, presumably, the proportion of plant P acquired from strongly sorbed sources decreased with inoculation, while the proportion from labile inorganic P increased. Implications for plant fitness under field conditions now require investigation.

A Linguistic Analysis of Spanglish: Relating Language to Identity.

According to the 2000 census, 35.3 million Hispanics live in the United States. This number comprises 12.5% of the overall population rendering the Latino community the largest minority in the United States. The Mexican community is not only the largest Hispanic group but also the fastest growing: from 1990 to 2000, the Mexican population grew 52.9% increasing from 13.5 million to 20.6 million (U.S. Department of Commerce News, 2001). The influx of Mexican immigrants coupled with the expansion of their community within the United States has created an unparalleled situation of language contact. Language is synonymous with identity (cf. Granger, 2004, and works cited within). To the extent that this is true, Spanish is synonymous with being Mexican and by extension, Chicano. With the advent of amnesty programs such as Immigration Reform and Control Act (IRCA), which naturalized millions of Mexican migrants, what was once a temporal migratory population has become increasingly permanent (Durand et al., 1999). In an effort to conserve Mexican traditions and identity, the struggle to preserve the mother tongue while at the same time acculturate to mainstream Americana has resulted in a variant of Spanglish that has received little attention. This paper will examine the variant of Spanglish seen in the greater Los Angeles area and liken it to the bi-national identity under which these Mexican Americans thrive.

Testosterone is associated with self-employment among Australian men

Testosterone has pronounced effects on men’s physiological development and smaller, more nuanced, impacts on their economic behavior. In this study of 1199 Australian adult males, we investigate the relationship between the self-employed and their serum testosterone levels. Because prior studies have identified that testosterone is a hormone that is responsive to external factors (e.g. competition, risk-taking), we explicitly control for omitted variable bias and reverse causality by using an instrumental variable approach. We use insulin as our primary instrument to account for endogeneity between testosterone and self-employment. This is because prior research has identified a relationship between insulin and testosterone but not between insulin and self-employment. Our results show that there is a positive association between total testosterone and self-employment. Robustness checks using bioavailable testosterone and another similar instrument (daily alcohol consumption) confirm this positive finding.

A simplified approach for Chaplygin-type cosmologies

A new class of accelerating cosmological models driven by a one-parameter version of the general Chaplygin-type equation of state is proposed. The simplified version is naturally obtained from causality considerations with basis on the adiabatic sound speed vs plus the observed accelerating stage of the universe. We show that very stringent constraints on the unique free parameter a describing the simplified Chaplygin model can be obtained from a joint analysis involving the latest SNe type la data and the recent Sloan Digital Sky Survey measurement of baryon acoustic oscillations (BAO). In our analysis we have considered separately the SNe type la gold sample measured by [A.G. Riess et al.. Astrophys. J. 607 (2004) 665] and the supernova legacy survey (SNLS) from [P. Astier et al., Astron. Astrophys. 447 (2006) 31]. At 95.4% (c.l.), we find for BAO + gold sample, 0.91 <= alpha <= 1.0 and Omega(m) = 0.28(-0.048)(+0.043) while BAO + SNLS analysis provides 0.94 <= alpha <= 1.0 and Omega(m) = 0.27(-0.045)(+0.048). (C) 2008 Elsevier B.V. All rights reserved.

Inferring Contagion in Regulatory Networks

Several gene regulatory network models containing concepts of directionality at the edges have been proposed. However, only a few reports have an interpretable definition of directionality. Here, differently from the standard causality concept defined by Pearl, we introduce the concept of contagion in order to infer directionality at the edges, i.e., asymmetries in gene expression dependences of regulatory networks. Moreover, we present a bootstrap algorithm in order to test the contagion concept. This technique was applied in simulated data and, also, in an actual large sample of biological data. Literature review has confirmed some genes identified by contagion as actually belonging to the TP53 pathway.

Residual-based test for Nonlinear Cointegration with application in PPPs

Nested by linear cointegration first provided in Granger (1981), the definition of nonlinear cointegration is presented in this paper. Sequentially, a nonlinear cointegrated economic system is introduced. What we mainly study is testing no nonlinear cointegration against nonlinear cointegration by residual-based test, which is ready for detecting stochastic trend in nonlinear autoregression models. We construct cointegrating regression along with smooth transition components from smooth transition autoregression model. Some properties are analyzed and discussed during the estimation procedure for cointegrating regression, including description of transition variable. Autoregression of order one is considered as the model of estimated residuals for residual-based test, from which the teststatistic is obtained. Critical values and asymptotic distribution of the test statistic that we request for different cointegrating regressions with different sample sizes are derived based on Monte Carlo simulation. The proposed theoretical methods and models are illustrated by an empirical example, comparing the results with linear cointegration application in Hamilton (1994). It is concluded that there exists nonlinear cointegration in our system in the final results.

Testing linear cointegration against smooth-transition cointegration

This paper studies a smooth-transition (ST) type cointegration. The proposed ST cointegration allows for regime switching structure in a cointegrated system. It nests the linear cointegration developed by Engle and Granger (1987) and the threshold cointegration studied by Balke and Fomby (1997). We develop F-type tests to examine linear cointegration against ST cointegration in ST-type cointegrating regression models with or without time trends. The null asymptotic distributions of the tests are derived with stationary transition variables in ST cointegrating regression models. And it is shown that our tests have nonstandard limiting distributions expressed in terms of standard Brownian motion when regressors are pure random walks, while have standard asymptotic distributions when regressors contain random walks with nonzero drift. Finite-sample distributions of those tests are studied by Monto Carlo simulations. The small-sample performance of the tests states that our F-type tests have a better power when the system contains ST cointegration than when the system is linearly cointegrated. An empirical example for the purchasing power parity (PPP) data (monthly US dollar, Italy lira and dollar-lira exchange rate from 1973:01 to 1989:10) is illustrated by applying the testing procedures in this paper. It is found that there is no linear cointegration in the system, but there exits the ST-type cointegration in the PPP data.

Testing Seasonal Unit Roots in Data at Any Frequency, an HEGY approach

This paper generalizes the HEGY-type test to detect seasonal unit roots in data at any frequency, based on the seasonal unit root tests in univariate time series by Hylleberg, Engle, Granger and Yoo (1990). We introduce the seasonal unit roots at first, and then derive the mechanism of the HEGY-type test for data with any frequency. Thereafter we provide the asymptotic distributions of our test statistics when different test regressions are employed. We find that the F-statistics for testing conjugation unit roots have the same asymptotic distributions. Then we compute the finite-sample and asymptotic critical values for daily and hourly data by a Monte Carlo method. The power and size properties of our test for hourly data is investigated, and we find that including lag augmentations in auxiliary regression without lag elimination have the smallest size distortion and tests with seasonal dummies included in auxiliary regression have more power than the tests without seasonal dummies. At last we apply the our test to hourly wind power production data in Sweden and shows there are no seasonal unit roots in the series.

Testing for Seasonal Unit Roots when Residuals Contain Serial Correlations under HEGY Test Framework

This paper introduces a corrected test statistic for testing seasonal unit roots when residuals contain serial correlations, based on the HEGY test proposed by Hylleberg,Engle, Granger and Yoo (1990). The serial correlations in the residuals of test regressionare accommodated by making corrections to the commonly used HEGY t statistics. Theasymptotic distributions of the corrected t statistics are free from nuisance parameters.The size and power properties of the corrected statistics for quarterly and montly data are investigated. Based on our simulations, the corrected statistics for monthly data havemore power compared with the commonly used HEGY test statistics, but they also have size distortions when there are strong negative seasonal correlations in the residuals.

Combinação de previsões de índices de preços

A combinação de previsões é caracterizada pelo aumento da precisão de prognósticos decorrente da complementaridade da informação contida nas previsões individuais. Este trabalho parte das idéias do consagrado artigo de Bates e Granger (1969) com o objetivo de investigar se há como elevar a precisão de previsões de índices de preços. Há evidências de que, embora os ganhos da combinação sejam limitados, os riscos decorrentes da combinação são menores que seus benefícios.

Indicadores antecedentes de atividade industrial no Brasil

Esta dissertação apresenta diferentes metodologias de construção de indicadores antecedentes compostos de atividade econômica comparando os resultados obtidos por cada de acordo com seu poder de antecipação dos movimentos cíclicos da indústria brasileira. Entre as metodologias testadas incluem-se: i) a tradicional, proposta pelo National Bureau of Economic Research (NBER) na década de 60, adaptada e melhorada ao longo dos anos por instituições como a OCDE, The Conference Board e outros; ii) a seleção de variáveis por meio de testes de causalidade de Granger, e iii) seleção e pesos determinados por meio de regressão múltipla. A qualidade dos indicadores antecedentes compostos criados foi avaliada fora da amostra, com base na sua capacidade em antecipar, de forma regular e estável, os pontos de reversão do ciclo de crescimento da indústria brasileira e levando em consideração a conformidade cíclica geral em relação à variável de referência.

Prevendo inflação usando séries temporais e combinações de previsões

O propósito deste estudo é analisar a capacidade dos modelos econométricos ARMA, ADL, VAR e VECM de prever inflação, a fim de verificar qual modelagem é capaz de realizar as melhores previsões num período de até 12 meses, além de estudar os efeitos da combinação de previsões. Dentre as categorias de modelos analisados, o ARMA (univariado) e o ADL (bivariado e multivariado), foram testados com várias combinações de defasagens. Foram realizadas previsões fora-da-amostra utilizando 3 períodos distintos da economia brasileira e os valores foram comparados ao IPCA realizado, a fim de verificar os desvios medidos através do EQM (erro quadrático médio). Combinações das previsões usando média aritmética, um método de média ponderada proposto por Bates e Granger (1969) e média ponderada através de regressão linear múltipla foram realizadas. As previsões também foram combinadas com a previsão do boletim FOCUS do Banco Central. O método de Bates e Granger minimiza a variância do erro da combinação e encontra uma previsão com variância do erro menor ou igual à menor variância dos erros das previsões individuais, se as previsões individuais forem não viesadas. A conclusão é que, com as técnicas de séries temporais utilizadas, alguns modelos individuais fornecem previsões com EQM relativamente baixos. Destacando-se, dentre eles, os modelos VAR e VECM. Porém, com a combinação de previsões os EQM obtidos são menores do que os das previsões individuais usadas para combinação. Na maioria dos casos, a combinação de previsões com o boletim FOCUS também melhorou significativamente os resultados e forneceu previsões com EQM menores do que os das previsões individuais, destacando-se, dentre os métodos de combinações utilizados, a combinação via regressão linear múltipla.