On the evolution of the oceanic component of the IPSL climate models from CMIP3 to CMIP5: A mean state comparison

This study analyses the impact on the oceanic mean state of the evolution of the oceanic component (NEMO) of the climate model developed at Institut Pierre Simon Laplace (IPSL-CM), from the version IPSL-CM4, used for third phase of the Coupled Model Intercomparison Project (CMIP3), to IPSL-CM5A, used for CMIP5. Several modifications have been implemented between these two versions, in particular an interactive coupling with a biogeochemical module, a 3-band model for the penetration of the solar radiation, partial steps at the bottom of the ocean and a set of physical parameterisations to improve the representation of the impact of turbulent and tidal mixing. A set of forced and coupled experiments is used to single out the effect of each of these modifications and more generally the evolution of the oceanic component on the IPSL coupled models family. Major improvements are located in the Southern Ocean, where physical parameterisations such as partial steps and tidal mixing reinforce the barotropic transport of water mass, in particular in the Antarctic Circumpolar Current) and ensure a better representation of Antarctic bottom water masses. However, our analysis highlights that modifications, which substantially improve ocean dynamics in forced configuration, can yield or amplify biases in coupled configuration. In particular, the activation of radiative biophysical coupling between biogeochemical cycle and ocean dynamics results in a cooling of the ocean mean state. This illustrates the difficulty to improve and tune coupled climate models, given the large number of degrees of freedom and the potential compensating effects masking some biases.

Cross-Country Evidence on Output Growth Volatility: Nonstationary Variance and GARCH Models

This paper revisits the issue of conditional volatility in real GDP growth rates for Canada, Japan, the United Kingdom, and the United States. Previous studies find high persistence in the volatility. This paper shows that this finding largely reflects a nonstationary variance. Output growth in the four countries became noticeably less volatile over the past few decades. In this paper, we employ the modified ICSS algorithm to detect structural change in the unconditional variance of output growth. One structural break exists in each of the four countries. We then use generalized autoregressive conditional heteroskedasticity (GARCH) specifications modeling output growth and its volatility with and without the break in volatility. The evidence shows that the time-varying variance falls sharply in Canada, Japan, and the U.K. and disappears in the U.S., excess kurtosis vanishes in Canada, Japan, and the U.S. and drops substantially in the U.K., once we incorporate the break in the variance equation of output for the four countries. That is, the integrated GARCH (IGARCH) effect proves spurious and the GARCH model demonstrates misspecification, if researchers neglect a nonstationary unconditional variance.

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Analysis of Melanoma Onset: Assessing Familial Aggregation by Using Estimating Equations and Fitting Variance Components via Bayesian Random Effects Models

We investigate whether relative contributions of genetic and shared environmental factors are associated with an increased risk in melanoma. Data from the Queensland Familial Melanoma Project comprising 15,907 subjects arising from 1912 families were analyzed to estimate the additive genetic, common and unique environmental contributions to variation in the age at onset of melanoma. Two complementary approaches for analyzing correlated time-to-onset family data were considered: the generalized estimating equations (GEE) method in which one can estimate relationship-specific dependence simultaneously with regression coefficients that describe the average population response to changing covariates; and a subject-specific Bayesian mixed model in which heterogeneity in regression parameters is explicitly modeled and the different components of variation may be estimated directly. The proportional hazards and Weibull models were utilized, as both produce natural frameworks for estimating relative risks while adjusting for simultaneous effects of other covariates. A simple Markov Chain Monte Carlo method for covariate imputation of missing data was used and the actual implementation of the Bayesian model was based on Gibbs sampling using the free ware package BUGS. In addition, we also used a Bayesian model to investigate the relative contribution of genetic and environmental effects on the expression of naevi and freckles, which are known risk factors for melanoma.

Integrated component scheduling models for chip shooter machines

This paper focuses on minimizing printed circuit board (PCB) assembly time for a chipshootermachine, which has a movable feeder carrier holding components, a movable X–Y table carrying a PCB, and a rotary turret with multiple assembly heads. The assembly time of the machine depends on two inter-related optimization problems: the component sequencing problem and the feeder arrangement problem. Nevertheless, they were often regarded as two individual problems and solved separately. This paper proposes two complete mathematical models for the integrated problem of the machine. The models are verified by two commercial packages. Finally, a hybrid genetic algorithm previously developed by the authors is presented to solve the model. The algorithm not only generates the optimal solutions quickly for small-sized problems, but also outperforms the genetic algorithms developed by other researchers in terms of total assembly time.

Using architecture models to support the generation and operation of component-based adaptive systems

Modelling architectural information is particularly important because of the acknowledged crucial role of software architecture in raising the level of abstraction during development. In the MDE area, the level of abstraction of models has frequently been related to low-level design concepts. However, model-driven techniques can be further exploited to model software artefacts that take into account the architecture of the system and its changes according to variations of the environment. In this paper, we propose model-driven techniques and dynamic variability as concepts useful for modelling the dynamic fluctuation of the environment and its impact on the architecture. Using the mappings from the models to implementation, generative techniques allow the (semi) automatic generation of artefacts making the process more efficient and promoting software reuse. The automatic generation of configurations and reconfigurations from models provides the basis for safer execution. The architectural perspective offered by the models shift focus away from implementation details to the whole view of the system and its runtime change promoting high-level analysis. © 2009 Springer Berlin Heidelberg.

Cognitive Component Skills of Reading Comprehension in Developing Readers

Die Fähigkeit, geschriebene Texte zu verstehen, d.h. eine kohärente mentale Repräsentation von Textinhalten zu erstellen, ist eine notwendige Voraussetzung für eine erfolgreiche schulische und außerschulische Entwicklung. Es ist daher ein zentrales Anliegen des Bildungssystems Leseschwierigkeiten frühzeitig zu diagnostizieren und mithilfe zielgerichteter Interventionsprogramme zu fördern. Dies erfordert ein umfassendes Wissen über die kognitiven Teilprozesse, die dem Leseverstehen zugrunde liegen, ihre Zusammenhänge und ihre Entwicklung. Die vorliegende Dissertation soll zu einem umfassenden Verständnis über das Leseverstehen beitragen, indem sie eine Auswahl offener Fragestellungen experimentell untersucht. Studie 1 untersucht inwieweit phonologische Rekodier- und orthographische Dekodierfertigkeiten zum Satz- und Textverstehen beitragen und wie sich beide Fertigkeiten bei deutschen Grundschüler(inne)n von der 2. bis zur 4. Klasse entwickeln. Die Ergebnisse legen nahe, dass beide Fertigkeiten signifikante und eigenständige Beiträge zum Leseverstehen leisten und dass sich ihr relativer Beitrag über die Klassenstufen hinweg nicht verändert. Darüber hinaus zeigt sich, dass bereits deutsche Zweitklässler(innen) den Großteil geschriebener Wörter in altersgerechten Texten über orthographische Vergleichsprozesse erkennen. Nichtsdestotrotz nutzen deutsche Grundschulkinder offenbar kontinuierlich phonologische Informationen, um die visuelle Worterkennung zu optimieren. Studie 2 erweitert die bisherige empirische Forschung zu einem der bekanntesten Modelle des Leseverstehens—der Simple View of Reading (SVR, Gough & Tunmer, 1986). Die Studie überprüft die SVR (Reading comprehension = Decoding x Comprehension) mithilfe optimierter und methodisch stringenter Maße der Modellkonstituenten und überprüft ihre Generalisierbarkeit für deutsche Dritt- und Viertklässler(innen). Studie 2 zeigt, dass die SVR einer methodisch stringenten Überprüfung nicht standhält und nicht ohne Weiteres auf deutsche Dritt- und Viertklässler(innen) generalisiert werden kann. Es wurden nur schwache Belege für eine multiplikative Verknüpfung von Dekodier- (D) und Hörverstehensfertigkeiten (C) gefunden. Der Umstand, dass ein beachtlicher Teil der Varianz im Leseverstehen (R) nicht durch D und C aufgeklärt werden konnte, deutet darauf hin, dass das Modell nicht vollständig ist und ggf. durch weitere Komponenten ergänzt werden muss. Studie 3 untersucht die Verarbeitung positiv-kausaler und negativ-kausaler Kohärenzrelationen bei deutschen Erst- bis Viertklässler(inne)n und Erwachsenen im Lese- und Hörverstehen. In Übereinstimmung mit dem Cumulative Cognitive Complexity-Ansatz (Evers-Vermeul & Sanders, 2009; Spooren & Sanders, 2008) zeigt Studie 3, dass die Verarbeitung negativ-kausaler Kohärenzrelationen und Konnektoren kognitiv aufwändiger ist als die Verarbeitung positiv-kausaler Relationen. Darüber hinaus entwickelt sich das Verstehen beider Kohärenzrelationen noch über die Grundschulzeit hinweg und ist für negativ-kausale Relationen am Ende der vierten Klasse noch nicht abgeschlossen. Studie 4 zeigt und diskutiert die Nützlichkeit prozess-orientierter Lesetests wie ProDi- L (Richter et al., in press), die individuelle Unterschiede in den kognitiven Teilfertigkeiten des Leseverstehens selektiv erfassen. Hierzu wird exemplarisch die Konstruktvalidität des ProDi-L-Subtests ‚Syntaktische Integration’ nachgewiesen. Mittels explanatorischer Item- Repsonse-Modelle wird gezeigt, dass der Test Fertigkeiten syntaktischer Integration separat erfasst und Kinder mit defizitären syntaktischen Fertigkeiten identifizieren kann. Die berichteten Befunde tragen zu einem umfassenden Verständnis der kognitiven Teilfertigkeiten des Leseverstehens bei, das für eine optimale Gestaltung des Leseunterrichts, für das Erstellen von Lernmaterialien, Leseinstruktionen und Lehrbüchern unerlässlich ist. Darüber hinaus stellt es die Grundlage für eine sinnvolle Diagnose individueller Leseschwierigkeiten und für die Konzeption adaptiver und zielgerichteter Interventionsprogramme zur Förderung des Leseverstehens bei schwachen Leser(inne)n dar.

Censored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution.

In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.

Um modelo estocástico combinado de previsão sazonal para a precipitação no Brasil

Este artigo discute um modelo de previsão combinada para a realização de prognósticos climáticos na escala sazonal. Nele, previsões pontuais de modelos estocásticos são agregadas para obter as melhores projeções no tempo. Utilizam-se modelos estocásticos autoregressivos integrados a médias móveis, de suavização exponencial e previsões por análise de correlações canônicas. O controle de qualidade das previsões é feito através da análise dos resíduos e da avaliação do percentual de redução da variância não-explicada da modelagem combinada em relação às previsões dos modelos individuais. Exemplos da aplicação desses conceitos em modelos desenvolvidos no Instituto Nacional de Meteorologia (INMET) mostram bons resultados e ilustram que as previsões do modelo combinado, superam na maior parte dos casos a de cada modelo componente, quando comparadas aos dados observados.

Additive genetic relationship of longevity with fertility and production traits in Nellore cattle based on bivariate models

Survival or longevity is an economically important trait in beef cattle. The main inconvenience for its inclusion in selection criteria is delayed recording of phenotypic data and the high computational demand for including survival in proportional hazard models. Thus, identification of a longevity-correlated trait that could be recorded early in life would be very useful for selection purposes. We estimated the genetic relationship of survival with productive and reproductive traits in Nellore cattle, including weaning weight (WW), post-weaning growth (PWG), muscularity (MUSC), scrotal circumference at 18 months (SC18), and heifer pregnancy (HP). Survival was measured in discrete time intervals and modeled through a sequential threshold model. Five independent bivariate Bayesian analyses were performed, accounting for cow survival and the five productive and reproductive traits. Posterior mean estimates for heritability (standard deviation in parentheses) were 0.55 (0.01) for WW, 0.25 (0.01) for PWG, 0.23 (0.01) for MUSC, and 0.48 (0.01) for SC18. The posterior mean estimates (95% confidence interval in parentheses) for the genetic correlation with survival were 0.16 (0.13-0.19), 0.30 (0.25-0.34), 0.31 (0.25-0.36), 0.07 (0.02-0.12), and 0.82 (0.78-0.86) for WW, PWG, MUSC, SC18, and HP, respectively. Based on the high genetic correlation and heritability (0.54) posterior mean estimates for HP, the expected progeny difference for HP can be used to select bulls for longevity, as well as for post-weaning gain and muscle score.

Comparison of different models to estimate genetic parameters for carcass traits in a commercial broiler line

The effect of genetic and non-genetic factors for carcass, breast meat and leg weights, and yields of a commercial broiler line were investigated using the restricted maximum likelihood method, considering four different animal models, including or excluding maternal genetic effect with covariance between direct and maternal genetic effects, and maternal permanent environmental effect. The likelihood ratio test was used to determine the most adequate model for each trait. For carcass, breast, and leg weight, and for carcass and breast yield, maternal genetic and permanent environmental effects as well as the covariance between direct and maternal genetic effects were significant. The estimates of direct and maternal heritability were 0.17 and 0.04 for carcass weight, 0.26 and 0.06 for breast weight, 0.22 and 0.02 for leg weight, 0.32 and 0.02 for carcass yield, and 0.52 and 0.04 for breast yield, respectively. For leg yield, maternal permanent environmental effect was important, in addition to direct genetic effects. For that trait, direct heritability and maternal permanent environmental variance as a proportion of the phenotypic variance were 0.43 and 0.02, respectively. The results indicate that ignoring maternal effects in the models, even though they were of small magnitude (0.02 to 0.06), tended to overestimate direct genetic variance and heritability for all traits.