Malaria on the Amazonian frontier: Transmission dynamics, risk factors, spatial distribution, and prospects for control

Little follow-up data on malaria transmission in communities originating from frontier settlements in Amazonia are available. Here we describe a cohort study in a frontier settlement in Acre, Brazil, where 509 subjects contributed 489.7 person-years of follow-up. The association between malaria morbidity during the follow-up and individual, household, and spatial covariates was explored with mixed-effects logistic regression models and spatial analysis. Incidence rates for Plasmodium vivax and Plasmodium falciparum malaria were 30.0/100 and 16.3/100 person-years at risk, respectively. Malaria morbidity was strongly associated with land clearing and farming, and decreased after five years of residence in the area, suggesting that clinical immunity develops among subjects exposed to low malaria endemicity. Significant spatial clustering of malaria was observed in the areas of most recent occupation, indicating that the continuous influx of nonimmune settlers to forest-fringe areas perpetuates the cycle of environmental change and colonization that favors malaria transmission in rural Amazonia.

Analysis of genotypic variation in genes associated with virulence in Aggregatibacter actinomycetemcomitans clinical isolates

Background and Objective: Although certain serotypes of Aggregatibacter actinomycetemcomitans are associated more with aggressive periodontitis than are other serotypes, the correlation between distinct lineages and virulence traits in this species is poorly understood. This study aimed to evaluate the polymorphism of genes encoding putative virulence factors of clinical isolates, and to correlate these findings with A. actinomycetemcomitans serotypes, genotypes and periodontal status of the hosts. Material and Methods: Twenty-six clinical isolates from diverse geographic populations with different periodontal conditions were evaluated. Genotyping was performed using pulse-field gel electrophoresis. Polymorphisms in the genes encoding leukotoxin, Aae, ApaH and determinants for serotype-specific O polysaccharide were investigated. Results: The isolates were classified into serotypes a-f, and exhibited three apaH genotypes, five aae alleles and 25 macrorestriction profiles. Two serotype b isolates (7.7%), obtained from Brazilian patients with aggressive periodontitis, were associated with the highly leukotoxic genotype; these isolates showed identical fingerprint patterns and aae and apaH genotypes. Serotype c, obtained from various periodontal conditions, was the most prevalent among Brazilian isolates, and isolates were distributed in two aae alleles, but formed a genetically distinct group based on apaH analysis. Cluster analysis showed a close relationship between fingerprinting genotypes and serotypes/apaH genotypes, but not with aae genotypes. Conclusion: Apart from the deletion in the ltx promoter region, no disease-associated markers were identified. Non-JP2-like strains recovered from individuals with periodontal disease exhibited considerable genetic variation regarding aae/apaH genotypes, serotypes and XhoI DNA fingerprints.

T3 rapidly modulates TSH beta mRNA stability and translational rate in the pituitary of hypothyroid rats

Whereas it is well known that T3 inhibits TSH beta gene transcription, its effects on TSH beta mRNA stability and translation have been poorly investigated. This study examined these possibilities, by evaluating the TSH beta transcripts poly(A) tail length, translational rate and binding to cytoskeleton, in pituitaries of thyroidectomized and sham-operated rats treated with T3 or saline, and killed 30 min thereafter. The hypothyroidism induced an increase of TSH beta transcript poly(A) tail, as well as of its content in ribosomes and attachment to cytoskeleton. The hypothyroid rats acutely treated with T3 exhibited a reduction of TSH beta mRNA poly(A) tail length and recruitment to ribosomes, indicating that this treatment decreased the stability and translation rate of TSH beta mRNA. Nevertheless, acute T3 administration to sham-operated rats provoked an increase of TSH beta transcripts binding to ribosomes. These data add new insight to an important role of T3 in rapidly regulating TSH gene expression at posttranscriptional level. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

A Community-based Survey of Human Toxoplasmosis in Rural Amazonia: Seroprevalence, Seroconversion Rate, and Associated Risk Factors

IgG antibodies to Toxoplasma gondii were detected in, March-April 2004, in 65.8% (95% confidence interval, 60.8-70.8%) of 342 systematically sampled subjects 5-90 years of age (87.5% of the eligible) living in a rural settlement in Amazonia, with a seroconversion rate of 9% over I year of follow-up of 99 seronegative subjects. Multiple logistic regression analysis identified age as the only significant independent predictor of seropositivity at the baseline. Each additional year of age increases the odds of being seropositive by 6%, and 76.8% of the subjects are expected to be seropositive at 30 years of age. A single high-prevalence spatial cluster, comprising 11.9% of the seropositive subjects, was detected in the area; households in the cluster were less likely to have dogs as pets and their heads had a lower education level, when compared with households located outside the cluster. The challenges for preventing human toxoplasmosis in tropical rural settings are discussed.

Role of glutamate NMDA receptors and nitric oxide located within the periaqueductal gray on defensive behaviors in mice confronted by predator

The midbrain periaqueductal gray (PAG) is part of the brain system involved in active defense reactions to threatening stimuli. Glutamate N-methyl-d-aspartate (NMDA) receptor activation within the dorsal column of the PAG (dPAG) leads to autonomic and behavioral responses characterized as the fear reaction. Nitric oxide (NO) has been proposed to be a mediator of the aversive action of glutamate, since the activation of NMDA receptors in the brain increases NO synthesis. We investigated the effects of intra-dPAG infusions of NMDA on defensive behaviors in mice pretreated with a neuronal nitric oxide synthase (nNOS) inhibitor [N omega-propyl-l-arginine (NPLA)], in the same midbrain site, during a confrontation with a predator in the rat exposure test (RET). Male Swiss mice received intra-dPAG injections of NPLA (0.1 or 0.4 nmol/0.1 mu l), and 10 min later, they were infused with NMDA (0.04 nmol/0.1 mu l) into the dPAG. After 10 min, each mouse was placed in the RET. NMDA treatment enhanced avoidance behavior from the predator and markedly increased freezing behavior. These proaversive effects of NMDA were prevented by prior injection of NPLA. Furthermore, defensive behaviors (e.g., avoidance, risk assessment, freezing) were consistently reduced by the highest dose of NPLA alone, suggesting an intrinsic effect of nitric oxide on defensive behavior in mice exposed to the RET. These findings suggest a potential role of glutamate NMDA receptors and NO in the dPAG in the regulation of defensive behaviors in mice during a confrontation with a predator in the RET.

Alignment-based extraction of multiword expressions

Due to idiosyncrasies in their syntax, semantics or frequency, Multiword Expressions (MWEs) have received special attention from the NLP community, as the methods and techniques developed for the treatment of simplex words are not necessarily suitable for them. This is certainly the case for the automatic acquisition of MWEs from corpora. A lot of effort has been directed to the task of automatically identifying them, with considerable success. In this paper, we propose an approach for the identification of MWEs in a multilingual context, as a by-product of a word alignment process, that not only deals with the identification of possible MWE candidates, but also associates some multiword expressions with semantics. The results obtained indicate the feasibility and low costs in terms of tools and resources demanded by this approach, which could, for example, facilitate and speed up lexicographic work.

An investigation into feature construction to assist word sense disambiguation

Identifying the correct sense of a word in context is crucial for many tasks in natural language processing (machine translation is an example). State-of-the art methods for Word Sense Disambiguation (WSD) build models using hand-crafted features that usually capturing shallow linguistic information. Complex background knowledge, such as semantic relationships, are typically either not used, or used in specialised manner, due to the limitations of the feature-based modelling techniques used. On the other hand, empirical results from the use of Inductive Logic Programming (ILP) systems have repeatedly shown that they can use diverse sources of background knowledge when constructing models. In this paper, we investigate whether this ability of ILP systems could be used to improve the predictive accuracy of models for WSD. Specifically, we examine the use of a general-purpose ILP system as a method to construct a set of features using semantic, syntactic and lexical information. This feature-set is then used by a common modelling technique in the field (a support vector machine) to construct a classifier for predicting the sense of a word. In our investigation we examine one-shot and incremental approaches to feature-set construction applied to monolingual and bilingual WSD tasks. The monolingual tasks use 32 verbs and 85 verbs and nouns (in English) from the SENSEVAL-3 and SemEval-2007 benchmarks; while the bilingual WSD task consists of 7 highly ambiguous verbs in translating from English to Portuguese. The results are encouraging: the ILP-assisted models show substantial improvements over those that simply use shallow features. In addition, incremental feature-set construction appears to identify smaller and better sets of features. Taken together, the results suggest that the use of ILP with diverse sources of background knowledge provide a way for making substantial progress in the field of WSD.

Texture analysis and classification using deterministic tourist walk

In this paper, we present a study on a deterministic partially self-avoiding walk (tourist walk), which provides a novel method for texture feature extraction. The method is able to explore an image on all scales simultaneously. Experiments were conducted using different dynamics concerning the tourist walk. A new strategy, based on histograms. to extract information from its joint probability distribution is presented. The promising results are discussed and compared to the best-known methods for texture description reported in the literature. (C) 2009 Elsevier Ltd. All rights reserved.

A complex network approach to text summarization

Automatic summarization of texts is now crucial for several information retrieval tasks owing to the huge amount of information available in digital media, which has increased the demand for simple, language-independent extractive summarization strategies. In this paper, we employ concepts and metrics of complex networks to select sentences for an extractive summary. The graph or network representing one piece of text consists of nodes corresponding to sentences, while edges connect sentences that share common meaningful nouns. Because various metrics could be used, we developed a set of 14 summarizers, generically referred to as CN-Summ, employing network concepts such as node degree, length of shortest paths, d-rings and k-cores. An additional summarizer was created which selects the highest ranked sentences in the 14 systems, as in a voting system. When applied to a corpus of Brazilian Portuguese texts, some CN-Summ versions performed better than summarizers that do not employ deep linguistic knowledge, with results comparable to state-of-the-art summarizers based on expensive linguistic resources. The use of complex networks to represent texts appears therefore as suitable for automatic summarization, consistent with the belief that the metrics of such networks may capture important text features. (c) 2008 Elsevier Inc. All rights reserved.

Complex networks analysis of manual and machine translations

Complex networks have been increasingly used in text analysis, including in connection with natural language processing tools, as important text features appear to be captured by the topology and dynamics of the networks. Following previous works that apply complex networks concepts to text quality measurement, summary evaluation, and author characterization, we now focus on machine translation (MT). In this paper we assess the possible representation of texts as complex networks to evaluate cross-linguistic issues inherent in manual and machine translation. We show that different quality translations generated by NIT tools can be distinguished from their manual counterparts by means of metrics such as in-(ID) and out-degrees (OD), clustering coefficient (CC), and shortest paths (SP). For instance, we demonstrate that the average OD in networks of automatic translations consistently exceeds the values obtained for manual ones, and that the CC values of source texts are not preserved for manual translations, but are for good automatic translations. This probably reflects the text rearrangements humans perform during manual translation. We envisage that such findings could lead to better NIT tools and automatic evaluation metrics.

Spectroscopic features of erbium-doped CaM2O6 (M = Nb, Ta) single crystal fibers grown by the laser-heated pedestal growth technique

Erbium-doped single crystal fibers, with low phonon energy and fairly high absorption and emission cross sections are interesting laser active media, for compact, near-infrared and/or upconversion lasers. In this work, high optical quality Er3+-doped CaNb2O6 and CaTa2O6 single crystal fibers were successfully grown by the versatile laser-heated pedestal growth technique, and characterized from the structural and spectroscopic points of view. The results indicate that these crystal fiber compositions, which had not been explored so far, offer potential applications, not only as laser active media, but also in other optical devices. (c) 2007 Elsevier B.V. All rights reserved.

Investigation of AISI 1040 steel corrosion H(2)S solution containing chloride ions by digital image processing coupled with in electrochemical techniques

This paper presents a study of AISI 1040 steel corrosion in aqueous electrolyte of acetic acid buffer containing 3.1 and 31 x 10(-3) mol dm(-3) of Na(2)S in both the presence and absence of 3.5 wt.% NaCl. This investigation of steel corrosion was carried out using potential polarization, and open-circuit and in situ optical microscopy. The morphological analysis and classification of types of surface corrosion damage by digital image processing reveals grain boundary corrosion and shows a non-uniform sulfide film growth, which occurs preferentially over pearlitic grains through successive formation and dissolution of the film. (C) 2011 Elsevier Ltd. All rights reserved.

How grain boundaries modify the high-temperature dielectric response of ferroelectric electroceramics like BaTiO(3)?

Dielectric properties of BaTiO(3) ferroelectric ceramics were studied over wide frequency and temperature ranges. The materials showed complex dielectric behaviors, which included an anomalous increase of permittivity towards higher temperatures. Important, this property tended however to saturate to values that varied with grain-boundary density. Application of impedance spectroscopy and consideration of the series-layer model allowed a coherent discussion of these and other interesting observations from this work. In particular, analysis of the relationship existing in this model between macroscopic and microscopic dielectric properties rendered possible to account for grain vs. grain-boundary dielectric behaviors, in harmony with microstructure features, and to know the dielectric anomaly strength to be in fact expected from grain boundaries in such polycrystalline materials. (C) 2010 Elsevier Ltd. All rights reserved.

Using metrics from complex networks to evaluate machine translation

Establishing metrics to assess machine translation (MT) systems automatically is now crucial owing to the widespread use of MT over the web. In this study we show that such evaluation can be done by modeling text as complex networks. Specifically, we extend our previous work by employing additional metrics of complex networks, whose results were used as input for machine learning methods and allowed MT texts of distinct qualities to be distinguished. Also shown is that the node-to-node mapping between source and target texts (English-Portuguese and Spanish-Portuguese pairs) can be improved by adding further hierarchical levels for the metrics out-degree, in-degree, hierarchical common degree, cluster coefficient, inter-ring degree, intra-ring degree and convergence ratio. The results presented here amount to a proof-of-principle that the possible capturing of a wider context with the hierarchical levels may be combined with machine learning methods to yield an approach for assessing the quality of MT systems. (C) 2010 Elsevier B.V. All rights reserved.

Thermal dependence of the zero-bias conductance through a nanostructure

We show that the conductance of a quantum wire side-coupled to a quantum dot, with a gate potential favoring the formation of a dot magnetic moment, is a universal function of the temperature. Universality prevails even if the currents through the dot and the wire interfere. We apply this result to the experimental data of Sato et al. (Phys. Rev. Lett., 95 (2005) 066801). Copyright (C) EPLA, 2009