Application of stable isotope analysis to differentiate shrimp extracted by industrial fishing or produced through aquaculture practices.

Carbon and nitrogen stable isotope values were determined in Pacific white shrimp (Litopenaeus vannamei) with the objective of discriminating animals produced through aquaculture practices from those extracted from the wild. Farmed animals were collected at semi-intensive shrimp farms in Mexico and Ecuador. Fisheries-derived shrimps were caught in different fishing areas representing two estuarine systems and four open sea locations in Mexico and Ecuador. Carbon and nitrogen stable isotope values (13CVPDB and 15NAIR) allowed clear differentiation of wild from farmed animals. 13CVPDB and 15NAIR values in shrimps collected in the open sea were isotopically enriched (−16.99‰ and 11.57‰), indicating that these organisms belong to higher trophic levels than farmed animals. 13CVPDB and 15NAIR values of farmed animals (−19.72‰ and 7.85‰, respectively) partially overlapped with values measured in animals collected in estuaries (−18.46‰ and 5.38‰, respectively). Canonical discriminant analysis showed that when used separately and in conjunction, 13CVPDB and I5NAIR values were powerful discriminatory variables and demonstrate the viability of isotopic evaluations to distinguish wild-caught shrimps from aquaculture shrimps. Methodological improvements will define a verification tool to support shrimp traceability protocols.

Exploring Hidden Coherent Feature Groups and Temporal Semantics for Multimedia Big Data Analysis

Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with a focus on rare event detection in videos. The proposed framework is able to explore hidden semantic feature groups in multimedia data and incorporate temporal semantics, especially for video event detection. First, a hierarchical semantic data representation is presented to alleviate the semantic gap issue, and the Hidden Coherent Feature Group (HCFG) analysis method is proposed to capture the correlation between features and separate the original feature set into semantic groups, seamlessly integrating multimedia data in multiple modalities. Next, an Importance Factor based Temporal Multiple Correspondence Analysis (i.e., IF-TMCA) approach is presented for effective event detection. Specifically, the HCFG algorithm is integrated with the Hierarchical Information Gain Analysis (HIGA) method to generate the Importance Factor (IF) for producing the initial detection results. Then, the TMCA algorithm is proposed to efficiently incorporate temporal semantics for re-ranking and improving the final performance. At last, a sampling-based ensemble learning mechanism is applied to further accommodate the imbalanced datasets. In addition to the multimedia semantic representation and class imbalance problems, lack of organization is another critical issue for multimedia big data analysis. In this framework, an affinity propagation-based summarization method is also proposed to transform the unorganized data into a better structure with clean and well-organized information. The whole framework has been thoroughly evaluated across multiple domains, such as soccer goal event detection and disaster information management.

Assessing brain connectivity through electroencephalographic signal processing and modeling analysis

Brain functioning relies on the interaction of several neural populations connected through complex connectivity networks, enabling the transmission and integration of information. Recent advances in neuroimaging techniques, such as electroencephalography (EEG), have deepened our understanding of the reciprocal roles played by brain regions during cognitive processes. The underlying idea of this PhD research is that EEG-related functional connectivity (FC) changes in the brain may incorporate important neuromarkers of behavior and cognition, as well as brain disorders, even at subclinical levels. However, a complete understanding of the reliability of the wide range of existing connectivity estimation techniques is still lacking. The first part of this work addresses this limitation by employing Neural Mass Models (NMMs), which simulate EEG activity and offer a unique tool to study interconnected networks of brain regions in controlled conditions. NMMs were employed to test FC estimators like Transfer Entropy and Granger Causality in linear and nonlinear conditions. Results revealed that connectivity estimates reflect information transmission between brain regions, a quantity that can be significantly different from the connectivity strength, and that Granger causality outperforms the other estimators. A second objective of this thesis was to assess brain connectivity and network changes on EEG data reconstructed at the cortical level. Functional brain connectivity has been estimated through Granger Causality, in both temporal and spectral domains, with the following goals: a) detect task-dependent functional connectivity network changes, focusing on internal-external attention competition and fear conditioning and reversal; b) identify resting-state network alterations in a subclinical population with high autistic traits. Connectivity-based neuromarkers, compared to the canonical EEG analysis, can provide deeper insights into brain mechanisms and may drive future diagnostic methods and therapeutic interventions. However, further methodological studies are required to fully understand the accuracy and information captured by FC estimates, especially concerning nonlinear phenomena.

[climacteric Syndrome In A Northeastern Brazilian City: A Household Survey].

To assess the prevalence of Climacteric Syndrome (CS) in women from a municipality of Northeastern Brazil which is less developed socioeconomically. A prospective household survey was performed in São Luís, Maranhão, Brazil with 1,210 climacteric women aged 45 to 60 years. Interviews were applied using previously tested standard questionnaires from April to July 2008. The severity of climacteric symptoms was analyzed by circulatory and psychological indexes and the latter were associated with menopausal status. Multiple correspondence analysis was used to assess the relation among climacteric symptoms. Most patients were 55 to 60 years old (35.3%), mulatto (37.9%), with 9-11 years of schooling (39.8%), with a partner (56%), Catholic (73.9%) and belonged to the socioeconomic class C (51.1%). The prevalence of CS was 85.9%, and hot flashes (56.4%) and sweating (50.4%) were the most prevalent symptoms. The most frequent psychological symptoms were nervousness (45%) and emotional liability (44.8%). The severity of vasomotor and psychological symptoms was significantly higher during the peri and postmenopausal period (p<0.05). Vaginal dryness (62.7%) was the most prevalent urogenital complaint. The prevalence of CS was high among women from São Luís, Maranhão, Brazil.

Diversidade de abelhas (Hymenoptera, Apidae) ao longo de um gradiente latitudinal na Mata Atlântica

A Mata Atlântica é um dos ambientes mais ricos e ameaçados do mundo, o que deveria ter estimulado em muito o estudo e a conservação do Bioma, mas a fauna de Hymenoptera permanece ainda relativamente pouco conhecida. Em especial, a fauna de abelhas da floresta ombrófila densa é pouco estudada em comparação à fauna das áreas abertas brasileiras. O projeto temático "Biodiversidade de Hymenoptera e Isoptera: riqueza e diversidade ao longo de um gradiente latitudinal na Mata Atlântica - a floresta úmida do leste do Brasil", integrante do Programa Biota-Fapesp, foi idealizado com o objetivo de catalogar térmitas, formigas e famílias selecionadas de vespas ao longo da Mata Atlântica, disponibilizando dados que permitam melhor embasar a conservação deste bioma. O protocolo de amostragem aplicada para a coleta de himenópteros (excluindo as formigas) empregou armadilhas Malaise, pratos-armadilha de cor amarela e esforço similar na varredura de vegetação ao longo de 17 localidades selecionadas, representando um gradiente de quase 20° de latitude na Mata Atlântica, dos Estados da Paraíba até Santa Catarina. Este protocolo foi definido para otimizar a coleta de vespas, sendo as abelhas um produto secundário da amostragem (levantamentos de abelhas em geral utilizam captura em flores ao longo das estações do ano). No entanto, devido à escala regional do projeto e ao grande esforço de amostragem, uma expressiva quantidade de abelhas foi coletada durante o projeto, incluindo novos registros de abelhas para a Mata Atlântica. Foi amostrado um total de 797 espécimes distribuídos em 105 espécies de abelhas; o grupo de abelhas mais rico e abundante foi Meliponina. Uma análise de correspondência "destendenciada" ('detrended correspondence analysis') aplicada à uma matriz de presença ou ausência de Meliponina revela a relativamente fraca influência do gradiente latitudinal na composição das assembléias de abelhas de Mata Atlântica. Uma listagem das espécies amostradas por localidade, com suas freqüências relativas, é apresentada e discutida.

Estádio sucessional e fatores geográficos como determinantes da similaridade florística entre comunidades florestais no Planalto Atlântico, Estado de São Paulo, Brasil

A análise das relações de similaridade florística entre comunidades geralmente conduz ao estabelecimento de padrões, condicionados por fatores diversos que determinam a ocorrência ou não das espécies em diferentes locais. Em busca de tais padrões, foram analisadas as relações de similaridade florística entre comunidades florestais localizadas na região do Planalto de Ibiúna, estado de São Paulo, Brasil. Incluíram-se na análise 21 fragmentos florestais e seis sítios em uma Reserva Florestal contínua, sendo que a composição florística e a estrutura da comunidade arbórea (DAP mínimo 5 cm) em cada local foram amostradas pelo método de quadrantes. Aplicaram-se dois métodos de análises multivariadas: 1) Análise de Correspondência Destendenciada (DCA), com base no índice de similaridade de Sørensen; e 2) Divisão Hierárquica Dicotômica (TWINSPAN). A similaridade florística foi mais elevada entre comunidades em estádios sucessionais semelhantes, especialmente se estivessem geograficamente próximas. Há um gradiente florístico associado à latitude, indicando tratar-se de uma região de transição entre biomas. Nos sítios situados na face norte da região de estudo estão presentes espécies que também ocorrem no cerradão e em floresta estacional semidecidual, enquanto nos sítios situados na face sul prevalecem espécies características da floresta ombrófila densa.

A assembléia de abelhas (Hymenoptera, Apidae) de uma área restrita de campos naturais do Parque Estadual de Vila Velha, Paraná e comparações com áreas de campos e cerrado

A assembléia de abelhas (Hymenoptera, Apidae) de uma área restrita de campos naturais do Parque Estadual de Vila Velha, Paraná e comparações com áreas de campos e cerrado. Foram realizadas coletas sistemáticas de abelhas em uma área restrita no Parque Estadual de Vila Velha, Paraná, no período de outubro de 2003 a setembro de 2004. Essa amostragem visou gerar subsídios para comparações entre áreas de campo dentro do Parque e com outras áreas de vegetação aberta brasileiras. A área de estudo possui cerca de quatro hectares e foi subdividida em quatro subáreas contínuas e com o mesmo perímetro. As abelhas em flores e em vôo foram capturadas com auxílio de rede entomológica. Foram coletados 1.459 espécimes pertencentes a 122 espécies de abelhas. Estas espécies estão distribuídas em 51 gêneros, 20 tribos e cinco subfamílias. As plantas visitadas correspondem a 93 espécies, pertencentes a 62 gêneros e 29 famílias. Neste estudo e em outro estudo realizado anteriormente em outra área do Parque foram coletadas 222 espécies sendo 74 espécies em comum as duas áreas e uma soma de 148 espécies restritas a uma ou outra área. Ainda, registros históricos de abelhas para Vila Velha elevam a riqueza conhecida para 261 espécies. O índice de similaridade de Morisita entre as áreas foi de 0,50 quando utilizadas as plantas como variáveis e 0,88 quando utilizados gêneros e espécies de abelhas, revelando uma notável heterogeneidade. Comparações entre as áreas do Parque Estadual de Vila Velha e áreas de campos e cerrado foram realizadas através do índice de similaridade e da análise de correspondência. Foram observados dois agrupamentos fortemente evidentes, referentes aos campos e ao cerrado. A análise de correspondência sugere que alguns gêneros podem ser relacionados a determinadas formações vegetais. Esse estudo indica que a fauna de abelhas de Vila Velha é composta principalmente por gêneros relacionados às áreas de campos, porém com presença de elementos de cerrado.

Análise proposicional quantitativa aplicada à pesquisa em administração

The analysis of interviews with open-ended questions is a common practice amongst researchers in the field of Management. The difficulty therein is to convert the linguistic data into categories or quantitative values for subsequent statistical treatment. Proposals made to this end generally entail counting lexical occurrences which, since they are founded on previously established meanings, fail to include semantic associations made by interviews. This article aims to present an analysis tool comprising a set of techniques apt to generate linguistic units that can be statistically described, compared, modeled and inferred: the Quantitative Propositional Analysis (QPA), Its main difference from other such methods lies in the choice of a proposition - and not the lexical unit - as analysis unit. We present the application of this method through a study about the international expansion of retail firms.

Characterizing chaotic melodies in automatic music composition

In this paper, we initially present an algorithm for automatic composition of melodies using chaotic dynamical systems. Afterward, we characterize chaotic music in a comprehensive way as comprising three perspectives: musical discrimination, dynamical influence on musical features, and musical perception. With respect to the first perspective, the coherence between generated chaotic melodies (continuous as well as discrete chaotic melodies) and a set of classical reference melodies is characterized by statistical descriptors and melodic measures. The significant differences among the three types of melodies are determined by discriminant analysis. Regarding the second perspective, the influence of dynamical features of chaotic attractors, e.g., Lyapunov exponent, Hurst coefficient, and correlation dimension, on melodic features is determined by canonical correlation analysis. The last perspective is related to perception of originality, complexity, and degree of melodiousness (Euler's gradus suavitatis) of chaotic and classical melodies by nonparametric statistical tests. (c) 2010 American Institute of Physics. [doi: 10.1063/1.3487516]

Greenhouse gases emission from soil contaminated with automobile industry residue in Brazil

Solid waste of the automobile industry containing large amounts of heavy metals might affect the emission of greenhouse gases (GHG) when applied to the soil. Accumulation of inorganic chemical elements in the environment generally occurs due to human activity (industry, agriculture, mining and waste landfills). Residues from human activities may release heavy metals to the soil solution, causing toxicity to plants and other soil organisms. Heavy metals may also be adsorbed to clay minerals and/or complexed by the soil organic matter, becoming a potential source of pollutants. Not much is known about the behavior of solid wastes in tropical soil as regarded as source of greenhouse gases (GHG). The emission of GHG (CO(2), CH(4) and N(2)O) was evaluated in incubated soil samples collected in an area contaminated with a solid residue from an automobile industry. Samples were randomly collected at 0 to 0.2 m (a mix of soil and residue), 0.2 to 0.4 m (only residue) and 0.4 to 0.6 m (only soil). A contiguous uncontaminated area, cultivated with sugarcane, was also sampled following the same protocol. Canonical Discriminant Analysis and Principal Component Analysis were applied to the data to evaluate the GHG emission rates. Emission rates of GHG were greater in the samples from the contaminated than the sugarcane area, particularly high during the first days of incubation. CO(2) emissions were greater in samples collected at the upper layer for both areas, while CH(4) and N(2)O emissions were similar in all samples. The emission rates of CH(4) were the most efficient variables to differentiate contaminated and uncontaminated areas.

Pricing corporate bonds in Brazil: 2000 to 2004

This paper analyzes the factors that influence the issuing price of debentures in Brazil in the period from year 2000 to 2004, applying a factor model, in which exogenous variables explain return and price behavior. The variables in this study include: rating, choice of index, maturity, country risk, basic interest rate, long-term and short-term rate spread, the stock market index, and the foreign exchange rate. Results indicate that the index variable, probability of default and bond`s maturity influence pricing and points out associations of long-term bonds with better rating issues. (C) 2008 Elsevier Inc. All rights reserved.

Fragmentation of a Neotropical migratory fish population by a century-old dam

Loss of connectivity in impounded rivers is among the impacts imposed by dams, and mitigation measures such as fish passages might not accomplish their purpose of reestablishing an efficient bi-directional gene flow in the fish populations affected. As a consequence, fish populations remain fragmented, and a new interpopulational structure may develop, with increased risk of reduced genetic diversity and stochastic extinction. In order to evaluate the effects of the Gavio Peixoto Dam, which was constructed almost a century ago on the Jacar,-Gua double dagger u River in the Upper Parana River basin, Brazil, a comparative morphometric study was undertaken on the populations of the Neotropical migratory characid fish Salminus hilarii living up- and downstream of this dam. Population dynamics, spatial segregation, and habitat use by different age classes were monitored for 2 years. We found that segregation caused by the dam and long periods with no efficient connection by fish passages have led to fragmentation and interpopulational structuring of S. hilarii, as revealed by canonical variable analysis of morphometric features. The fish populations occupying the up- and downstream sections have succeeded in performing short-distance reproductive migrations in the main river and tributaries, have found suitable habitats for completing their life cycle, and have been able to maintain distinct small-sized populations so far.

Diversidade e prospecção de fungos endofíticos de Begonia spp. encontradas na Mata Atlântica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Entrepreneurship Education : The role of the Higher Education Institutions in the Entrepreneurial Attitudes of the Students

8th International Conference of Education, Research and Innovation. 18-20 November, 2015, Seville, Spain.

Arrow plot and CA maps on microarray preprocessing methods

Microarray allow to monitoring simultaneously thousands of genes, where the abundance of the transcripts under a same experimental condition at the same time can be quantified. Among various available array technologies, double channel cDNA microarray experiments have arisen in numerous technical protocols associated to genomic studies, which is the focus of this work. Microarray experiments involve many steps and each one can affect the quality of raw data. Background correction and normalization are preprocessing techniques to clean and correct the raw data when undesirable fluctuations arise from technical factors. Several recent studies showed that there is no preprocessing strategy that outperforms others in all circumstances and thus it seems difficult to provide general recommendations. In this work, it is proposed to use exploratory techniques to visualize the effects of preprocessing methods on statistical analysis of cancer two-channel microarray data sets, where the cancer types (classes) are known. For selecting differential expressed genes the arrow plot was used and the graph of profiles resultant from the correspondence analysis for visualizing the results. It was used 6 background methods and 6 normalization methods, performing 36 pre-processing methods and it was analyzed in a published cDNA microarray database (Liver) available at http://genome-www5.stanford.edu/ which microarrays were already classified by cancer type. All statistical analyses were performed using the R statistical software.