Resampling methods for parameter-free and robust feature selection with mutual information

Combining the mutual information criterion with a forward feature selection strategy offers a good trade-off between optimality of the selected feature subset and computation time. However, it requires to set the parameter(s) of the mutual information estimator and to determine when to halt the forward procedure. These two choices are difficult to make because, as the dimensionality of the subset increases, the estimation of the mutual information becomes less and less reliable. This paper proposes to use resampling methods, a K-fold cross-validation and the permutation test, to address both issues. The resampling methods bring information about the variance of the estimator, information which can then be used to automatically set the parameter and to calculate a threshold to stop the forward procedure. The procedure is illustrated on a synthetic dataset as well as on real-world examples

UML Reflections

The UML shares with reflective architectures the idea that self-definition of languages and systems is a key principle for building and maintaining complex systems. The UML is now defined by a four-layer metalevel structure, enabling a flexible and extensible definition of models by metamodels, and even a self-description of the meta-metamodel (the MOF). This metalevel dimension of UML is currently restricted to structural reflection. But recently a new extension to the UML, called the Action Semantics (AS), has been proposed for standardization to the OMG. This paper explores how this proposed extension brings a behavioural reflection dimension to the UML. Indeed, we show that it is not only possible but quite e#ective to use the AS for manipulating UML models (including the AS metamodel). Besides elegant conceptual achievements, such as a metacircular definition of the AS, reflective modeling with the AS leverages on the UML metalevel architecture to provide the benefits of a reflective approach, in terms of separation of concerns, within a mainstream industrial context. A complete model can now be built as an ideal model representing the core concepts in the application, to which non-functional requirements are integrated as fully traceable transformations over this ideal model. For example, this approach paves the way for powerful UML-defined semantics-based model transformations such as refactoring, aspect weaving, application of design patterns or round-trip engineering

Evidence for an increase in cosmogenic 10Be during a geomagnetic reversal

Reversals in the geomagnetic field, which occur every few hundred thousand years, represent a dramatic change in the Earth's environment. Although there is no satisfactory theory for such reversals, it is generally accepted that the dipole field intensity decreases to <20% of its 'normal' value for a few thousand years during the change in direction. Because the galactic and solar cosmic rays which impinge on the Earth's atmosphere are charged, a significant fraction (about half) of them are deflected by the geomagnetic field. At the time of a reversal, this magnetic shielding is greatly reduced, and it has been suggested that the increased flux of high-energy particles could have effects on evolutionary or climatic processes. For example, the statistically significant coincidence in levels of some marine faunal extinctions and reversal boundaries in ocean sediments could be caused, directly or indirectly, by the decreased geomagnetic intensity during the reversal. We report here evidence in marine sediments for an increase in cosmogenic 10Be production in the Earth's atmosphere during the Brunhes-Matuyama reversal 730,000 yr ago. In addition to confirming an increase in cosmogenic isotope production, the results provide information on the magnitude and duration of the geomagnetic intensity decrease during such an event, and the depth at which remanent magnetism is acquired in marine sediments

Genetic Dissection of an Exogenously Induced Biofilm in Laboratory and Clinical Isolates of E. coli

Microbial biofilms are a dominant feature of many human infections. However, developing effective strategies for controlling biofilms requires an understanding of the underlying biology well beyond what currently exists. Using a novel strategy, we have induced formation of a robust biofilm in Escherichia coli by utilizing an exogenous source of poly-N-acetylglucosamine (PNAG) polymer, a major virulence factor of many pathogens. Through microarray profiling of competitive selections, carried out in both transposon insertion and over-expression libraries, we have revealed the genetic basis of PNAG-based biofilm formation. Our observations reveal the dominance of electrostatic interactions between PNAG and surface structures such as lipopolysaccharides. We show that regulatory modulation of these surface structures has significant impact on biofilm formation behavior of the cell. Furthermore, the majority of clinical isolates which produced PNAG also showed the capacity to respond to the exogenously produced version of the polymer

Staphylococcus aureus RNAIII Binds to Two Distant Regions of coa mRNA to Arrest Translation and Promote mRNA Degradation

Staphylococcus aureus RNAIII is the intracellular effector of the quorum sensing system that temporally controls a large number of virulence factors including exoproteins and cell-wall-associated proteins. Staphylocoagulase is one major virulence factor, which promotes clotting of human plasma. Like the major cell surface protein A, the expression of staphylocoagulase is strongly repressed by the quorum sensing system at the post-exponential growth phase. Here we used a combination of approaches in vivo and in vitro to analyze the mechanism used by RNAIII to regulate the expression of staphylocoagulase. Our data show that RNAIII represses the synthesis of the protein through a direct binding with the mRNA. Structure mapping shows that two distant regions of RNAIII interact with coa mRNA and that the mRNA harbors a conserved signature as found in other RNAIII-target mRNAs. The resulting complex is composed of an imperfect duplex masking the Shine-Dalgarno sequence of coa mRNA and of a loop-loop interaction occurring downstream in the coding region. The imperfect duplex is sufficient to prevent the formation of the ribosomal initiation complex and to repress the expression of a reporter gene in vivo. In addition, the double-strand-specific endoribonuclease III cleaves the two regions of the mRNA bound to RNAIII that may contribute to the degradation of the repressed mRNA. This study validates another direct target of RNAIII that plays a role in virulence. It also illustrates the diversity of RNAIII-mRNA topologies and how these multiple RNAIII-mRNA interactions would mediate virulence regulation

Testing the predictive ability of corridor implied volatility under GARCH models

YesThis paper studies the predictive ability of corridor implied volatility (CIV) measure. It is motivated by the fact that CIV is measured with better precision and reliability than the model-free implied volatility due to the lack of liquid options in the tails of the risk-neutral distribution. By adding CIV measures to the modified GARCH specifications, the out-of-sample predictive ability of CIV is measured by the forecast accuracy of conditional volatility. It finds that the narrowest CIV measure, covering about 10% of the RND, dominate the 1-day ahead conditional volatility forecasts regardless of the choice of GARCH models in high volatile period; as market moves to non volatile periods, the optimal width broadens. For multi-day ahead forecasts narrow and mid-range CIV measures are favoured in the full sample and high volatile period for all forecast horizons, depending on which loss functions are used; whereas in non turbulent markets, certain mid-range CIV measures are favoured, for rare instances, wide CIV measures dominate the performance. Regarding the comparisons between best performed CIV measures and two benchmark measures (market volatility index and at-the-money Black–Scholes implied volatility), it shows that under the EGARCH framework, none of the benchmark measures are found to outperform best performed CIV measures, whereas under the GARCH and NAGARCH models, best performed CIV measures are outperformed by benchmark measures for certain instances