Patterns and processes of diversification in a widespread and ecologically diverse avian group, the buteonine hawks (Aves, Accipitridae)

Buteonine hawks represent one of the most diverse groups in the Accipitridae, with 58 species distributed in a variety of habitats on almost all continents. Variations in migratory behavior, remarkable dispersal capability, and unusual diversity in Central and South America make buteonine hawks an excellent model for studies in avian evolution. To evaluate the history of their global radiation, we used an integrative approach that coupled estimation of the phylogeny using a large sequence database (based on 6411 bp of mitochondrial markers and one nuclear intron from 54 species), divergence time estimates, and ancestral state reconstructions. Our findings suggest that Neotropical buteonines resulted from a long evolutionary process that began in the Miocene and extended to the Pleistocene. Colonization of the Nearctic, and eventually the Old World, occurred from South America, promoted by the evolution of seasonal movements and development of land bridges. Migratory behavior evolved several times and may have contributed not only to colonization of the Holarctic, but also derivation of insular species. In the Neotropics, diversification of the buteonines included four disjunction events across the Andes. Adaptation of monophyletic taxa to wet environments occurred more than once, and some relationships indicate an evolutionary connection among mangroves, coastal and varzea environments. On the other hand, groups occupying the same biome, forest, or open vegetation habitats are not monophyletic. Refuges or sea-level changes or a combination of both was responsible for recent speciation in Amazonian taxa. In view of the lack of concordance between phylogeny and classification, we propose numerous taxonomic changes. (C) 2009 Elsevier Inc. All rights reserved.

Demographic processes in the montane Atlantic rainforest: Molecular and cytogenetic evidence from the endemic frog Proceratophrys boiei

Historical climatic refugia predict genetic diversity in lowland endemics of the Brazilian Atlantic rainforest. Yet, available data reveal distinct biological responses to the Last Glacial Maximum (LGM) conditions across species of different altitudinal ranges. We show that species occupying Brazil's montane forests were significantly less affected by LGM conditions relative to lowland specialists, but that pre-Pleistocene tectonics greatly influenced their geographic variation. Our conclusions are based on palaeoclimatic distribution models, molecular sequences of the cytochrome b, 16S, and RAG-1 genes, and karyotype data for the endemic frog Proceratophrys boiei. DNA and chromosomal data identify in P. boiei at least two broadly divergent phylogroups, which have not been distinguished morphologically. Cytogenetic results also indicate an area of hybridization in southern Sao Paulo. The location of the phylogeographic break broadly matches the location of a NW-SE fault, which underwent reactivation in the Neogene and led to remarkable landscape changes in southeastern Brazil. Our results point to different mechanisms underpinning diversity patterns in lowland versus montane tropical taxa, and help us to understand the processes responsible for the large number of narrow endemics currently observed in montane areas of the southern Atlantic forest hotspot. (C) 2011 Elsevier Inc. All rights reserved.

Analysis of NDVI time series using cross-correlation and forecasting methods for monitoring sugarcane fields in Brazil

Brazil is the largest sugarcane producer in the world and has a privileged position to attend to national and international market places. To maintain the high production of sugarcane, it is fundamental to improve the forecasting models of crop seasons through the use of alternative technologies, such as remote sensing. Thus, the main purpose of this article is to assess the results of two different statistical forecasting methods applied to an agroclimatic index (the water requirement satisfaction index; WRSI) and the sugarcane spectral response (normalized difference vegetation index; NDVI) registered on National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite images. We also evaluated the cross-correlation between these two indexes. According to the results obtained, there are meaningful correlations between NDVI and WRSI with time lags. Additionally, the adjusted model for NDVI presented more accurate results than the forecasting models for WRSI. Finally, the analyses indicate that NDVI is more predictable due to its seasonality and the WRSI values are more variable making it difficult to forecast.

Signal propagation in Bayesian networks and its relationship with intrinsically multivariate predictive variables

A set of predictor variables is said to be intrinsically multivariate predictive (IMP) for a target variable if all properly contained subsets of the predictor set are poor predictors of the. target but the full set predicts the target with great accuracy. In a previous article, the main properties of IMP Boolean variables have been analytically described, including the introduction of the IMP score, a metric based on the coefficient of determination (CoD) as a measure of predictiveness with respect to the target variable. It was shown that the IMP score depends on four main properties: logic of connection, predictive power, covariance between predictors and marginal predictor probabilities (biases). This paper extends that work to a broader context, in an attempt to characterize properties of discrete Bayesian networks that contribute to the presence of variables (network nodes) with high IMP scores. We have found that there is a relationship between the IMP score of a node and its territory size, i.e., its position along a pathway with one source: nodes far from the source display larger IMP scores than those closer to the source, and longer pathways display larger maximum IMP scores. This appears to be a consequence of the fact that nodes with small territory have larger probability of having highly covariate predictors, which leads to smaller IMP scores. In addition, a larger number of XOR and NXOR predictive logic relationships has positive influence over the maximum IMP score found in the pathway. This work presents analytical results based on a simple structure network and an analysis involving random networks constructed by computational simulations. Finally, results from a real Bayesian network application are provided. (C) 2012 Elsevier Inc. All rights reserved.

COMMUNITY OF ORIGIN EFFECTS ON VIRTUAL BRAND COMMUNITIES PARTICIPANT

The question about the effectiveness of companies in maintaining their own communities versus benefiting from the ones owned by consumers remains open. We examine differences between firm-managed and customer-managed brand communities regarding the impact of perceived psychographic homogeneity, availability of virtual avenues and relationship with the brand on the community's influence on members and the assessments and intentions of community participants. Data were obtained from 555 respondents in two leading Microsoft XBOX brand communities in Brazil. Results indicate that management of the community of origin is the moderator of all considered relationships. Also, the most favorable effects for the company occur in the community that is not directly controlled and managed by the company itself. Brand loyalty, however, is higher for members of the official brand community. Guidelines on how companies can benefit from consumer-managed communities are discussed.

MOOGLE: a metamodel-based model search engine

Models are becoming increasingly important in the software development process. As a consequence, the number of models being used is increasing, and so is the need for efficient mechanisms to search them. Various existing search engines could be used for this purpose, but they lack features to properly search models, mainly because they are strongly focused on text-based search. This paper presents Moogle, a model search engine that uses metamodeling information to create richer search indexes and to allow more complex queries to be performed. The paper also presents the results of an evaluation of Moogle, which showed that the metamodel information improves the accuracy of the search.

Phylogeography of an Atlantic forest passerine reveals demographic stability through the last glacial maximum

In this study we analyzed the phylogeographic pattern and historical demography of an endemic Atlantic forest (AF) bird, Basileuterus leucoblepharus, and test the influence of the last glacial maximum (LGM) on its population effective size using coalescent simulations. We address two main questions: (i) Does B. leucoblepharus present population genetic structure congruent with the patterns observed for other AF organisms? (ii) How did the LGM affect the effective population size of B. leucoblepharus? We sequenced 914 bp of the mitochondrial gene cytochrome b and 512 bp of the nuclear intron 5 of beta-fibrinogen of 62 individuals from 15 localities along the AF. Both molecular markers revealed no genetic structure in B. leucoblepharus. Neutrality tests based on both loci showed significant demographic expansion. The extended Bayesian skyline plot showed that the species seems to have experienced demographic expansion starting around 300,000 years ago, during the late Pleistocene. This date does not coincide with the LGM and the dynamics of population size showed stability during the LGM. To further test the effect of the LGM on this species, we simulated seven demographic scenarios to explore whether populations suffered specific bottlenecks. The scenarios most congruent with our data were population stability during the LGM with bottlenecks older than this period. This is the first example of an AF organism that does not show phylogeographic breaks caused by vicariant events associated to climate change and geotectonic activities in the Quaternary. Differential ecological, environmental tolerances and habitat requirements are possibly influencing the different evolutionary histories of these organisms. Our results show that the history of organism diversification in this megadiverse Neotropical forest is complex. Crown Copyright (c) 2012 Published by Elsevier Inc. All rights reserved.

Prevalência de anomalias congênitas associadas às fissuras labiopalatinas

Objetivo: Verificar a prevalência de anomalias congênitas associadas às fissuras labiopalatinas em crianças de 0 a 3 anos de idade. Métodos: Estudo transversal, observacional, aprovado pelo Comitê de Ética em Pesquisa (Ofício nº 412/2011). Participaram do estudo 325 mulheres, mães biológicas de crianças com fissuras labiopalatinas de 0 a 3 anos de idade, associadas ou não a anomalias congênitas, matriculados no HRAC-USP. A média de idade das mães foi de 29 anos e mediana de 28 anos. O tamanho amostral foi segundo a “Fórmula para cálculo de tamanho de amostra - Populações infinitas”. Os resultados foram tabulados em planilha do programa computacional Microsoft® Excel, apresentados em tabelas apontando a média, mediana, frequência absoluta (fi), frequência absoluta acumulada (Fi), frequência relativa acumulada (Fr). Para a comparação entre a porcentagem do agravo na população e amostra, utilizou-se o teste estatístico “Teste Exato de Fisher”, adotando-se nível de significância de 5%. Resultado: Quanto à prevalência de anomalias congênitas associadas às fissuras labiopalatinas, 209(64,30%) crianças na faixa etária de 0 a 3 anos, apresentaram fissura labiopalatina isolada e 116(35,69%) apresentaram algum tipo de anomalia congênita associada a essas fissuras. A fissura mais prevalente foi a fissura pós-forame, apresentando-se isolada em 63 casos e associadas à anomalias em 42 casos, seguida da fissura trans-forame incisivo unilateral esquerda, sendo 17 casos isolada e 59 casos associada à anomalias. A anomalia congênita associada às fissuras mais encontrada foi a Sequencia de Pierre Robin, seguida das cardiopatias diversas e malformações de pés e mãos. Conclusão: a prevalência de anomalias congênitas associadas às fissuras labiopalatinas foi de 35,69%.

CID: an efficient complexity-invariant distance for time series

The ubiquity of time series data across almost all human endeavors has produced a great interest in time series data mining in the last decade. While dozens of classification algorithms have been applied to time series, recent empirical evidence strongly suggests that simple nearest neighbor classification is exceptionally difficult to beat. The choice of distance measure used by the nearest neighbor algorithm is important, and depends on the invariances required by the domain. For example, motion capture data typically requires invariance to warping, and cardiology data requires invariance to the baseline (the mean value). Similarly, recent work suggests that for time series clustering, the choice of clustering algorithm is much less important than the choice of distance measure used.In this work we make a somewhat surprising claim. There is an invariance that the community seems to have missed, complexity invariance. Intuitively, the problem is that in many domains the different classes may have different complexities, and pairs of complex objects, even those which subjectively may seem very similar to the human eye, tend to be further apart under current distance measures than pairs of simple objects. This fact introduces errors in nearest neighbor classification, where some complex objects may be incorrectly assigned to a simpler class. Similarly, for clustering this effect can introduce errors by “suggesting” to the clustering algorithm that subjectively similar, but complex objects belong in a sparser and larger diameter cluster than is truly warranted.We introduce the first complexity-invariant distance measure for time series, and show that it generally produces significant improvements in classification and clustering accuracy. We further show that this improvement does not compromise efficiency, since we can lower bound the measure and use a modification of triangular inequality, thus making use of most existing indexing and data mining algorithms. We evaluate our ideas with the largest and most comprehensive set of time series mining experiments ever attempted in a single work, and show that complexity-invariant distance measures can produce improvements in classification and clustering in the vast majority of cases.

QuMinS: fast and scalable querying, mining and summarizing multi-modal databases

Given a large image set, in which very few images have labels, how to guess labels for the remaining majority? How to spot images that need brand new labels different from the predefined ones? How to summarize these data to route the user’s attention to what really matters? Here we answer all these questions. Specifically, we propose QuMinS, a fast, scalable solution to two problems: (i) Low-labor labeling (LLL) – given an image set, very few images have labels, find the most appropriate labels for the rest; and (ii) Mining and attention routing – in the same setting, find clusters, the top-'N IND.O' outlier images, and the 'N IND.R' images that best represent the data. Experiments on satellite images spanning up to 2.25 GB show that, contrasting to the state-of-the-art labeling techniques, QuMinS scales linearly on the data size, being up to 40 times faster than top competitors (GCap), still achieving better or equal accuracy, it spots images that potentially require unpredicted labels, and it works even with tiny initial label sets, i.e., nearly five examples. We also report a case study of our method’s practical usage to show that QuMinS is a viable tool for automatic coffee crop detection from remote sensing images.