Florestas estacionais e áreas de ecótono no estado do Tocantins, Brasil: parâmetros estruturais, classificação das fitofisionomias florestais e subsídios para conservação

O objetivo deste estudo foi descrever a riqueza, estrutura e diversidade de espécies arbóreas em áreas de Floresta Estacional e ecótono (Floresta Estacional/Floresta Ombrófila) no estado do Tocantins, buscando subsídios para a conservação, manejo florestal, compensação de reserva legal e recuperação ambiental, além de discutir as identidades fitogeográficas em comparação com outras florestas do Brasil. Em 18 bacias hidrográficas, conduziu-se amostragem da vegetação arbórea (DAP > 5 cm) de 22 áreas (amostras) por meio do inventário de 477 parcelas de 400 m². Foram elaboradas análises de classificação pelo método TWINSPAN, em duas escalas distintas. A primeira avaliou a diversidade beta entre as parcelas amostradas no estado do Tocantins e a segunda buscou analisar a similaridade das florestas do Tocantins em relação a outras florestas do bioma Cerrado e suas áreas de tensão ecológica. As florestas amostradas apresentaram ampla variação em termos de riqueza (33 a 243 espécies), densidade (486 a 1.179 ind.ha-1), área basal (14,04 e 37,49 m².ha-1), índices de diversidade (H´ = 2,75 a 4,59) e de equabilidade (J´= 0,72 a 0,86). As análises de classificação convergiram para resultados comuns, identificando quatro ambientes dissimilares em termos florísticos e estruturais no estado do Tocantins: Floresta Estacional Decidual, Floresta Estacional Semidecidual, ecótono Floresta Estacional Semidecidual/Floresta Ombrófila e ecótono Floresta Estacional Decidual/Floresta Ombrófila. A fim de manter a diversidade de plantas e de ambientes na região de transição Floresta Amazônica e Cerrado, sugere-se que o processo de criação de unidades de conservação no estado do Tocantins deva ser intensificado e tenha como base para seleção das áreas critérios biogeográficos.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Singularities of the dynamical structure factors of the spin-1/2 XXX chain at finite magnetic field

We study the longitudinal and transverse spin dynamical structure factors of the spin-1/2 XXX chain at finite magnetic field h, focusing in particular on the singularities at excitation energies in the vicinity of the lower thresholds. While the static properties of the model can be studied within a Fermi-liquid like description in terms of pseudoparticles, our derivation of the dynamical properties relies on the introduction of a form of the ‘pseudofermion dynamical theory’ (PDT) of the 1D Hubbard model suitably modified for the spin-only XXX chain and other models with two pseudoparticle Fermi points. Specifically, we derive the exact momentum and spin-density dependences of the exponents ζτ(k) controlling the singularities for both the longitudinal  and transverse (τ = t) dynamical structure factors for the whole momentum range  , in the thermodynamic limit. This requires the numerical solution of the integral equations that define the phase shifts in these exponents expressions. We discuss the relation to neutron scattering and suggest new experiments on spin-chain compounds using a carefully oriented crystal to test our predictions.

Vanishing spin stiffness in the spin-1/2 Heisenberg chain for any nonzero temperature

Whether at the zero spin density m = 0 and finite temperatures T > 0 the spin stiffness of the spin-1/2 XXX chain is finite or vanishes remains an unsolved and controversial issue, as different approaches yield contradictory results. Here we explicitly compute the stiffness at m = 0 and find strong evidence that it vanishes. In particular, we derive an upper bound on the stiffness within a canonical ensemble at any fixed value of spin density m that is proportional to m2L in the thermodynamic limit of chain length L → ∞, for any finite, nonzero temperature, which implies the absence of ballistic transport for T > 0 for m = 0. Although our method relies in part on the thermodynamic Bethe ansatz (TBA), it does not evaluate the stiffness through the second derivative of the TBA energy eigenvalues relative to a uniform vector potential. Moreover, we provide strong evidence that in the thermodynamic limit the upper bounds on the spin current and stiffness used in our derivation remain valid under string deviations. Our results also provide strong evidence that in the thermodynamic limit the TBA method used by X. Zotos [Phys. Rev. Lett. 82, 1764 (1999)] leads to the exact stiffness values at finite temperature T > 0 for models whose stiffness is finite at T = 0, similar to the spin stiffness of the spin-1/2 Heisenberg chain but unlike the charge stiffness of the half-filled 1D Hubbard model.

Analysis of physicochemical interaction between the components of asphalt mixtures with rubber

Tese de Doutoramento em Engenharia Civil

Psychiatric morbidity and quality of life of primary care attenders in two cities in Brazil

Objective: To identify the associations among quality of life (QoL), social determinants and psychological distress in primary care in two cities in Brazil. Methods: A cross-sectional study with 1,466 patients from 2009 to 2010. The statistical analysis used the t-test to compare the variables of interest to the study. Results: The prevalence of Common Mental Disorders (CMD3), severe forms of Common Mental Disorders (CMD5), anxiety and depression were 20.5%, 32%, 37% and 25.1% respectively. Thes presence of psychological distress is associated with worse QoL among the patients studied, especially those older than 40 years of age. In cases of CMD3, those with higher income and educational levels presented higher QoL in the psychical and psychological domains. For the cases of probable anxiety, those with higher educational levels presented lower scores on the physical and social relationship scores. Conclusion: Psychological distress can be associated with a worse QoL among those studied and can be influenced by socioeconomic conditions. Therefore, it is important to structure patient-centered help, which should also include patients’ social contexts.

Reconstruction of the regulatory network for Bacillus subtilis and reconciliation with gene expression data

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb. 2016.00275

Tapping the wealth of microbial data in high-throughput metabolic model reconstruction

Genome-scale metabolic models are valuable tools in the metabolic engineering process, based on the ability of these models to integrate diverse sources of data to produce global predictions of organism behavior. At the most basic level, these models require only a genome sequence to construct, and once built, they may be used to predict essential genes, culture conditions, pathway utilization, and the modifications required to enhance a desired organism behavior. In this chapter, we address two key challenges associated with the reconstruction of metabolic models: (a) leveraging existing knowledge of microbiology, biochemistry, and available omics data to produce the best possible model; and (b) applying available tools and data to automate the reconstruction process. We consider these challenges as we progress through the model reconstruction process, beginning with genome assembly, and culminating in the integration of constraints to capture the impact of transcriptional regulation. We divide the reconstruction process into ten distinct steps: (1) genome assembly from sequenced reads; (2) automated structural and functional annotation; (3) phylogenetic tree-based curation of genome annotations; (4) assembly and standardization of biochemistry database; (5) genome-scale metabolic reconstruction; (6) generation of core metabolic model; (7) generation of biomass composition reaction; (8) completion of draft metabolic model; (9) curation of metabolic model; and (10) integration of regulatory constraints. Each of these ten steps is documented in detail.

An R package for the integrated analysis of metabolomics and spectral data

Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.

Examen classis dioeciae.

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Examen classis dioeciae.

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Examen classis dioeciae.

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La izquierda latinoamericana en su laberinto: ¿entre el radicalismo y la moderación? Manejo de coaliciones y política económico-social en Chile, Bolivia y la Argentina, 2001-2009

La creciente literatura sobre el “giro a la izquierda” en América Latina ha dejado en un llamativo descuido el tratamiento de los factores políticos involucrados en la política económica de los gobiernos de la así llamada Nueva Izquierda latinoamericana. En este proyecto, sobre la base y la crítica de los escasos estudios sobre la temática, nos proponemos abordar la economía política de aquellos gobiernos a partir de una estrategia comparativa de tres casos que consideramos paradigmáticos: Chile, Argentina y Bolivia. Apoyándonos analíticamente en las nociones de coaliciones y de manejo de coaliciones, desarrollamos las hipótesis de que: 1) los gobiernos de la Nueva Izquierda responden a tres tipos diferentes según las características originales de su coalición de apoyo; 2) que los gobiernos tienden a implementar políticas económico-sociales compatibles con estas características cuya “cara izquierda” puede ser incompleta si tales características así lo exigen, y 3) que el mantenimiento, los cambios y eventual crisis de estas políticas se relaciona con los desequilibrios propios de cada tipo de gobierno y el intento de reequilibrio por parte de este a través del manejo -decisiones económicas y políticas orientadas a producir redistribuciones de recursos y a incentivar la continuidad o cambio de comportamientos económicos y políticos, respectivamente- de su coalición de apoyo. Con la guía de estas hipótesis procedemos, siguiendo la estrategia de process tracing, a la especificación de los mecanismos involucrados en los procesos de cada caso seleccionado con el fin de avanzar en el desarrollo de una teoría tipológica.