New perspectives on the synoptic and mesoscale structure of Hurricane Catarina

This work explores in detail synoptic and mesoscale features of Hurricane Catarina during its life cycle from a decaying baroclinic wave to a tropical depression that underwent tropical transition (TT) and finally to a Category 2 hurricane at landfall over Santa Catarina State coast, southern Brazil. This unique system caused 11 deaths mostly off the Brazilian coast and an estimated half billion dollars in damage in a matter of a few hours on 28 March 2004. Although the closest meteorological station available was tens of kilometres away from the eye, in situ meteorological measurements provided by a work-team sent to the area where the eye made landfall unequivocally reproduces the tropical signature with category 2 strength, adding to previous analysis where this data was not available. Further analyses are based mostly on remote sensing data available at the time of the event. A classic dipole blocking set synoptic conditions for Hurricane Catarina to develop, dynamically contributing to the low wind shear observed. On the other hand, on its westward transit, large scale subsidence limited its strength and vertical development. Catarina had relatively cool SST conditions, but this was mitigated by favourable air-sea fluxes leading to latent heat release-driven processes during the mature phase. The ocean`s dynamic topography also suggested the presence of nearby warm core rings which may have facilitated the transition and post-transition intensification. Since there were no records of such a system at least in the past 30 years and given that SSTs were generally below 26 degrees C and vertical shear was usually strong, despite all satellite data available, the system was initially classified as an extratropical cyclone. Here we hypothesise that this categorization was based oil inadequate regional scale model outputs which did not account for the importance of the latent heat fluxes over the ocean. Hurricane Catarina represents a dramatic event on weather systems in South America. It has attracted attention worldwide and poses questions as whether or not it is a symptom of global warming. (C) 2009 Elsevier B.V. All rights reserved.

Laterally transferred genomic islands in Xanthomonadales related to pathogenicity and primary metabolism

Lateral gene transfer (LGT) is considered as one of the drivers in bacterial genome evolution, usually associated with increased fitness and/or changes in behavior, especially if one considers pathogenic vs. non-pathogenic bacterial groups. The genomes of two phytopathogens, Xanthomonas campestris pv. campestris and Xanthomonas axonopodis pv. citri, were previously inspected for genome islands originating from LGT events, and, in this work, potentially early and late LGT events were identified according to their altered nucleotide composition. The biological role of the islands was also assessed, and pathogenicity, virulence and secondary metabolism pathways were functions highly represented, especially in islands that were found to be recently transferred. However, old islands are composed of a high proportion of genes related to cell primary metabolic functions. These old islands, normally undetected by traditional atypical composition analysis, but confirmed as product of LGT by atypical phylogenetic reconstruction, reveal the role of LGT events by replacing core metabolic genes normally inherited by vertical processes.

Image indexing and retrieval using an ART-2A neural network architecture

Traditional content-based image retrieval (CBIR) systems use low-level features such as colors, shapes, and textures of images. Although, users make queries based on semantics, which are not easily related to such low-level characteristics. Recent works on CBIR confirm that researchers have been trying to map visual low-level characteristics and high-level semantics. The relation between low-level characteristics and image textual information has motivated this article which proposes a model for automatic classification and categorization of words associated to images. This proposal considers a self-organizing neural network architecture, which classifies textual information without previous learning. Experimental results compare the performance results of the text-based approach to an image retrieval system based on low-level features. (c) 2008 Wiley Periodicals, Inc.

Cross-situational learning of object-word mapping using Neural Modeling Fields

The issue of how children learn the meaning of words is fundamental to developmental psychology. The recent attempts to develop or evolve efficient communication protocols among interacting robots or Virtual agents have brought that issue to a central place in more applied research fields, such as computational linguistics and neural networks, as well. An attractive approach to learning an object-word mapping is the so-called cross-situational learning. This learning scenario is based on the intuitive notion that a learner can determine the meaning of a word by finding something in common across all observed uses of that word. Here we show how the deterministic Neural Modeling Fields (NMF) categorization mechanism can be used by the learner as an efficient algorithm to infer the correct object-word mapping. To achieve that we first reduce the original on-line learning problem to a batch learning problem where the inputs to the NMF mechanism are all possible object-word associations that Could be inferred from the cross-situational learning scenario. Since many of those associations are incorrect, they are considered as clutter or noise and discarded automatically by a clutter detector model included in our NMF implementation. With these two key ingredients - batch learning and clutter detection - the NMF mechanism was capable to infer perfectly the correct object-word mapping. (C) 2009 Elsevier Ltd. All rights reserved.

How language can help discrimination in the Neural Modelling Fields framework

The relationship between thought and language and, in particular, the issue of whether and how language influences thought is still a matter of fierce debate. Here we consider a discrimination task scenario to study language acquisition in which an agent receives linguistic input from an external teacher, in addition to sensory stimuli from the objects that exemplify the overlapping categories that make up the environment. Sensory and linguistic input signals are fused using the Neural Modelling Fields (NMF) categorization algorithm. We find that the agent with language is capable of differentiating object features that it could not distinguish without language. In this sense, the linguistic stimuli prompt the agent to redefine and refine the discrimination capacity of its sensory channels. (C) 2007 Elsevier Ltd. All rights reserved.

Screening the Schistosoma mansoni transcriptome for genes differentially expressed in the schistosomulum stage in search for vaccine candidates

Schistosomiasis affects more than 200 million people worldwide; another 600 million are at risk of infection. The schistosomulum stage is believed to be the target of protective immunity in the attenuated cercaria vaccine model. In an attempt to identify genes up-regulated in the schistosomulum stage in relation to cercaria, we explored the Schistosoma mansoni transcriptome by looking at the relative frequency of reads in EST libraries from both stages. The 400 genes potentially up-regulated in schistosomula were analyzed as to their Gene Ontology categorization, and we have focused on those encoding-predicted proteins with no similarity to proteins of other organisms, assuming they could be parasite-specific proteins important for survival in the host. Up-regulation in schistosomulum relative to cercaria was validated with real-time reverse transcription polymerase chain reaction (RT-PCR) for five out of nine selected genes (56%). We tested their protective potential in mice through immunization with DNA vaccines followed by a parasite challenge. Worm burden reductions of 16-17% were observed for one of them, indicating its protective potential. Our results demonstrate the value and caveats of using stage-associated frequency of ESTs as an indication of differential expression coupled to DNA vaccine screening in the identification of novel proteins to be further investigated as potential vaccine candidates.