Approximation and support theorem for a wave equation in two space dimensions

We prove a characterization of the support of the law of the solution for a stochastic wave equation with two-dimensional space variable, driven by a noise white in time and correlated in space. The result is a consequence of an approximation theorem, in the convergence of probability, for equations obtained by smoothing the random noise. For some particular classes of coefficients, approximation in the Lp-norm for p¿1 is also proved.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

Keeping the Vermin Out: Perceived Disease Threat and Ideological Orientations as Predictors of Exclusionary Immigration Attitudes

Integrating evolutionary and social representations theories, the current study examines the relationship between perceived disease threat and exclusionary immigration attitudes in the context of a potential avian influenza pandemic. This large-scale disease provides a realistic context for investigating the link between disease threat and immigration attitudes. The main aim of this cross-sectional study (N=412) was to explore mechanisms through which perceived chronic and contextual disease threats operate on immigration attitudes. Structural equation models show that the relationship between chronic disease threat (germ aversion) and exclusionary immigration attitudes (assimiliationist immigration criteria, health-based immigration criteria and desire to reduce the proportion of foreigners) was mediated by ideological and normative beliefs (social dominance orientation, belief in a dangerous world), but not by contextual disease threat (appraisal of avian influenza pandemic threat). Contextual disease threat only predicted support for health-based immigration criteria. The conditions under which real-life disease threats influence intergroup attitudes are scrutinized. Convergence and dissimilarity of evolutionary and social representational approaches in accounting for the link between disease threat and immigration attitudes are discussed.

GDP and life expectancy in Italy and Spain over the long-run (1861-2008): insights from a timeseries approach

The article presents and discusses long-run series of per capita GDP and life expectancy for Italy and Spain (1861-2008). After refining the available estimates in order to make them comparable and with the avail of the most up-to-date researches, the main changes in the international economy and in technological and sociobiological regimes are used as analytical frameworks to re-assess the performances of the two countries; then structural breaks are searched for and Granger causality between the two variables is investigated. The long-run convergence notwithstanding, significant cyclical differences between the two countries can be detected: Spain began to modernize later in GDP, with higher volatility in life expectancy until recent decades; by contrast, Italy showed a more stable pattern of life expectancy, following early breaks in per capita GDP, but also a negative GDP break in the last decades. Our series confirm that, whereas at the early stages of development differences in GDP tend to mirror those in life expectancy, this is no longer true at later stages of development, when, if any, there seems to be a negative correlation between GDP and life expectancy: this finding is in line with the thesis of a non-monotonic relation between life expectancy and GDP and is supported by tests of Granger causality.

Evolutionary insights on C4 photosynthetic subtypes in grasses from genomics and phylogenetics

In plants, an oligogene family encodes NADP-malic enzymes (NADP-me), which are responsible for various functions and exhibit different kinetics and expression patterns. In particular, a chloroplast isoform of NADP-me plays a key role in one of the three biochemical subtypes of C4 photosynthesis, an adaptation to warm environments that evolved several times independently during angiosperm diversification. By combining genomic and phylogenetic approaches, this study aimed at identifying the molecular mechanisms linked to the recurrent evolutions of C4-specific NADP-me in grasses (Poaceae). Genes encoding NADP-me (nadpme) were retrieved from genomes of model grasses and isolated from a large sample of C3 and C4 grasses. Genomic and phylogenetic analyses showed that 1) the grass nadpme gene family is composed of four main lineages, one of which is expressed in plastids (nadpme-IV), 2) C4-specific NADP-me evolved at least five times independently from nadpme-IV, and 3) some codons driven by positive selection underwent parallel changes during the multiple C4 origins. The C4 NADP-me being expressed in chloroplasts probably constrained its recurrent evolutions from the only plastid nadpme lineage and this common starting point limited the number of evolutionary paths toward a C4 optimized enzyme, resulting in genetic convergence. In light of the history of nadpme genes, an evolutionary scenario of the C4 phenotype using NADP-me is discussed.

Initialisation of Nonlinearities for PNL and Wiener systems Inversion

This paper proposes a very fast method for blindly initial- izing a nonlinear mapping which transforms a sum of random variables. The method provides a surprisingly good approximation even when the basic assumption is not fully satis¯ed. The method can been used success- fully for initializing nonlinearity in post-nonlinear mixtures or in Wiener system inversion, for improving algorithm speed and convergence.

Translation and validation of the Ten-Item-Personality Inventory into spanish and catalan

In response to an increasing need for ever-shorter personality instruments, Gosling, Rentfrow, and Swann (2003) developed the Ten-Item-Personality Inventory (TIPI), which measures the dimensions of the Five Factor Model (FFM) using 10 items (two for each dimension) and can be administered in about one minute. In two studies and using a multi-judge (self and observer) and multi-instrument design, we develop Spanish (Castilian) and Catalan versions of the TIPI and evaluate them in terms of internal consistency, test-retest reliability, convergent, discriminant, and content validity, as well as self-observer correlations. Test-retest correlations were strong, and convergence with the NEO-PI-R factors was significant. There were also strong correlations between observer ratings and the participants’ self-ratings. Despite some inconsistencies with respect to the Agreeableness scale, the Catalan translation and both translations into Spanish of the original TIPI demonstrated sufficient psychometric properties to warrant use as a Five Factor personality measure when the use of longer instruments is not convenient or possible. Furthermore, as the first translation of a brief standard Big Five Instrument into Catalan, this work should facilitate future research on personality in the Catalan-speaking population.

Calmodulin kinase IV: expression and function during rat brain development.

The expression of calmodulin kinase IV (CaMKIV) can be induced by the thyroid hormone T3 in a time- and concentration-dependent manner at a very early stage of brain differentiation using a fetal rat telencephalon primary cell culture system which can grow and differentiate under chemically defined conditions (Krebs et al. (1996) J. Biol. Chem. 271, 11055-11058). After the induction of CaMKIV by T3 we examined the influence of prolonged absence of T3 from the culture medium on the expression of CaMKIV. We could demonstrate that after the T3-dependent induction of CaMKIV, omission of the hormone, even for 8 days, from the medium did not downregulate the expression of CaMKIV indicating that different regulatory mechanisms became important for the expression of the enzyme. We further showed that CaMKIV could be involved in the Ca(2+) -dependent expression of the immediate early gene c-fos, probably via phosphorylation of the transcription factor CREB. Convergence of signal transduction pathways on this transcription factor by using different protein kinases may explain the importance of CREB for the regulation of different cellular processes.

The homeostatic psyche: Freudian theory and somatic markers.

After years of reciprocal lack of interest, if not opposition, neuroscience and psychoanalysis are poised for a renewed dialogue. This article discusses some aspects of the Freudian metapsychology and its link with specific biological mechanisms. It highlights in particular how the physiological concept of homeostasis resonates with certain fundamental concepts of psychoanalysis. Similarly, the authors underline how the Freud and Damasio theories of brain functioning display remarkable complementarities, especially through their common reference to Meynert and James. Furthermore, the Freudian theory of drives is discussed in the light of current neurobiological evidences of neural plasticity and trace formation and of their relationships with the processes of homeostasis. The ensuing dynamics between traces and homeostasis opens novel avenues to consider inner life in reference to the establishment of fantasies unique to each subject. The lack of determinism, within a context of determinism, implied by plasticity and reconsolidation participates in the emergence of singularity, the creation of uniqueness and the unpredictable future of the subject. There is a gap in determinism inherent to biology itself. Uniqueness and discontinuity: this should today be the focus of the questions raised in neuroscience. Neuroscience needs to establish the new bases of a "discontinuous" biology. Psychoanalysis can offer to neuroscience the possibility to think of discontinuity. Neuroscience and psychoanalysis meet thus in an unexpected way with regard to discontinuity and this is a new point of convergence between them.

Structural macro factors and the affine term structure of interest rates

This work consists of three essays investigating the ability of structural macroeconomic models to price zero coupon U.S. government bonds. 1. A small scale 3 factor DSGE model implying constant term premium is able to provide reasonable a fit for the term structure only at the expense of the persistence parameters of the structural shocks. The test of the structural model against one that has constant but unrestricted prices of risk parameters shows that the exogenous prices of risk-model is only weakly preferred. We provide an MLE based variance-covariance matrix of the Metropolis Proposal Density that improves convergence speeds in MCMC chains. 2. Affine in observable macro-variables, prices of risk specification is excessively flexible and provides term-structure fit without significantly altering the structural parameters. The exogenous component of the SDF is separating the macro part of the model from the term structure and the good term structure fit has as a driving force an extremely volatile SDF and an implied average short rate that is inexplicable. We conclude that the no arbitrage restrictions do not suffice to temper the SDF, thus there is need for more restrictions. We introduce a penalty-function methodology that proves useful in showing that affine prices of risk specifications are able to reconcile stable macro-dynamics with good term structure fit and a plausible SDF. 3. The level factor is reproduced most importantly by the preference shock to which it is strongly and positively related but technology and monetary shocks, with negative loadings, are also contributing to its replication. The slope factor is only related to the monetary policy shocks and it is poorly explained. We find that there are gains in in- and out-of-sample forecast of consumption and inflation if term structure information is used in a time varying hybrid prices of risk setting. In-sample yield forecast are better in models with non-stationary shocks for the period 1982-1988. After this period, time varying market price of risk models provide better in-sample forecasts. For the period 2005-2008, out of sample forecast of consumption and inflation are better if term structure information is incorporated in the DSGE model but yields are better forecasted by a pure macro DSGE model.

Confirmatory factor analysis of an integrated model of psycopathology assessed with MMPI-2-RF and the MCMI-III

We presented an integrated hierarchical model of psychopathology that more accurately captures empirical patterns of comorbidity between clinical syndromes and personality disorders.In order to verify the structural validity of the model proposed, this study aimed to analyze the convergence between the Restructured Clinical (RC) scales and Personality scales (PSY-5) of the MMPI-2-RF and the Clinical Syndrome and Personality Disorder scales of the MCMI-III.The MMPI-2-RF and MCMI-III were administered to a clinical sample of 377 outpatients (167 men and 210 women).The structural hypothesiswas assessed by using a Confirmatory Factor Analytic design with four common superordinate factors. An independent-cluster-basis solution was proposed based on maximum likelihood estimation and the application of several fit indices.The fit of the proposed model can be considered as good and more so if we take into account its complexity.

Do fire and seed additions alter strong seed timing and priority effects on prairie establishment?, 2011

Many prairie restoration projects are hampered by a lack of knowledge on how to restore the high diversity found in prairies, while at the same time preventing the establishment of a large weedy component. Methods are needed to increase diversity and abundance of native species while minimizing exotic species invasions in both 1) newly planted restorations and 2) established restorations. We established an experiment in Story and Monona counties in 2005 to determine the effects of different native cover crop species and timing of seeding on the establishment of new prairie restorations. We found that adding a 30-species prairie mix in early spring led to diverse native communities, but adding the mix in the late summer or the following year after cover crops established led to low diversity communities dominated by exotics. The identity of cover crops affected communities less than timing of seed additions. A second seed addition added to ash after a spring fire in the seventh year (Monona County site) increased recruitment from the prairie mix slightly, but the increase was not enough to cause convergence in the treatments. Surprisingly, the second seed addition increased diversity only in communities that were already the most diverse (i.e., in plots seeded with the prairie mix in early spring before cover crops established). These results imply that 1) cover crops are not effective for establishing prairie and 2) over seeding into established plots may not be an easy and efficient way to increase native recruitment and lower weedy species abundances. Therefore, focusing on establishing high levels of recruitment and diversity and excluding weedy species during the critical time early in establishment should be a priority for new projects.

On the convergence of EM-like algorithms for image segmentation using Markov random fields.

Inference of Markov random field images segmentation models is usually performed using iterative methods which adapt the well-known expectation-maximization (EM) algorithm for independent mixture models. However, some of these adaptations are ad hoc and may turn out numerically unstable. In this paper, we review three EM-like variants for Markov random field segmentation and compare their convergence properties both at the theoretical and practical levels. We specifically advocate a numerical scheme involving asynchronous voxel updating, for which general convergence results can be established. Our experiments on brain tissue classification in magnetic resonance images provide evidence that this algorithm may achieve significantly faster convergence than its competitors while yielding at least as good segmentation results.

Collective symbolic coping with disease threat and othering: A case study of avian influenza

Much research studies how individuals cope with disease threat by blaming out-groups and protecting the in-group. The model of collective symbolic coping (CSC) describes four stages by which representations of a threatening event are elaborated in the mass media: awareness, divergence, convergence, and normalization. We used the CSC model to predict when symbolic in-group protection (othering) would occur in the case of the avian influenza (AI) outbreak. Two studies documented CSC stages and showed that othering occurred during the divergence stage, characterized by an uncertain symbolic environment. Study 1 analysed media coverage of AI over time, documenting CSC stages of awareness and divergence. In Study 2, a two-wave repeated cross-sectional survey was conducted just after the divergence stage and a year later. Othering was measured by the number of foreign countries erroneously ticked by participants as having human victims. Individual differences in germ aversion and social dominance orientation interacted to predict othering during the divergence stage but not a year later. Implications for research on CSC and symbolic in-group protection strategies resulting from disease threat are discussed.

Intrinsic subspace convergence in TDD MIMO communication

In numerical linear algebra, students encounter earlythe iterative power method, which finds eigenvectors of a matrixfrom an arbitrary starting point through repeated normalizationand multiplications by the matrix itself. In practice, more sophisticatedmethods are used nowadays, threatening to make the powermethod a historical and pedagogic footnote. However, in the contextof communication over a time-division duplex (TDD) multipleinputmultiple-output (MIMO) channel, the power method takes aspecial position. It can be viewed as an intrinsic part of the uplinkand downlink communication switching, enabling estimationof the eigenmodes of the channel without extra overhead. Generalizingthe method to vector subspaces, communication in thesubspaces with the best receive and transmit signal-to-noise ratio(SNR) is made possible. In exploring this intrinsic subspace convergence(ISC), we show that several published and new schemes canbe cast into a common framework where all members benefit fromthe ISC.