Famílias e alunos de origem africana no Maranhão do século XIX

This article demonstrates the existence of black families and the presence of children from these families in public schools of Maranhão, in the nineteenth century. Based on a conjectural methodology newspapers ads of the nineteenth century were consulted and also codices relating to records of baptism, marriage, and documentation of the Government Secretary, located in the Public Archives of the State of Maranhão and Public Library Benedito Leite.

La mortalidad de la población nativa del Brasil

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Déficit cuasifiscal: el caso argentino (1977-1989)

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Efficiency analysis of an isolated high voltage gain converter operating in resonant and non-resonant mode

This paper presents an efficiency investigation of an isolated high step-up ratio dc-dc converter aimed to be used for energy processing from low-voltage high-current energy sources, like batteries, photovoltaic modules or fuel-cells. The considered converter consists of an interleaved active clamp flyback topology combined with a voltage multiplier at the transformer secondary side capable of two different operating modes, i.e. resonant and non-resonant according to the design of the output capacitors. The main goal of this paper is to compare these two operating modes from the component losses point of view with the aim of maximize the overall converter efficiency. The approach is based on losses prediction using steady-state theoretical models (designed in Mathcad environment), taking into account both conduction and switching losses. The models are compared with steady-state simulations and experimental results considering different operating modes to validate the approach. © 2012 IEEE.

Predição da potência aeróbia (VO 2máx) de crianças e adolescentes em teste incremental na esteira rolante

The maximal oxygen uptake (VO2max) is the maximal quantity of energy that can be produced by the aerobic metabolism in certain time unity. It can be determined direct or indirectly by predictive equations. The objective of this study was to make a specific predictive equation to determine the VO 2max from boys aged 10-16 years-old. Forty-two boys underwent a treadmill running ergospirometric test, with the initial velocity set at 9 km/h, until voluntary exhaustion. By the multiple linear regression was possible to develop the following equation for the indirect determination of the VO 2max: VO2max (ml/min) = -1574.06 + (141.38 x Vpeak) + (48.34 * Body mass), with standard error of estimate = 191.5 ml/min (4.10 ml/kg/min) and coefficient of determination = 0.934. We suggest that this formula is appropriate to predict VO2max for this population.

Modelling fungus dispersal scenarios using cellular automata

This study focused on representing spatio-temporal patterns of fungal dispersal using cellular automata. Square lattices were used, with each site representing a host for a hypothetical fungus population. Four possible host states were allowed: resistant, permissive, latent or infectious. In this model, the probability of infection for each of the healthy states (permissive or resistant) in a time step was determined as a function of the host's susceptibility, seasonality, and the number of infectious sites and the distance between them. It was also assumed that infected sites become infectious after a pre-specified latency period, and that recovery is not possible. Several scenarios were simulated to understand the contribution of the model's parameters and the spatial structure on the dynamic behaviour of the modelling system. The model showed good capability for representing the spatio-temporal pattern of fungus dispersal over planar surfaces. With a specific problem in mind, the model can be easily modified and used to describe field behaviour, which can contribute to the conservation and development of management strategies for both natural and agricultural systems. © 2012 Elsevier B.V.

A computer vision approach to quantify leaf anatomical plasticity: A case study on gochnatia polymorpha (less.) cabrera

Inferences about leaf anatomical characteristics had largely been made by manually measuring diverse leaf regions, such as cuticle, epidermis and parenchyma to evaluate differences caused by environmental variables. Here we tested an approach for data acquisition and analysis in ecological quantitative leaf anatomy studies based on computer vision and pattern recognition methods. A case study was conducted on Gochnatia polymorpha (Less.) Cabrera (Asteraceae), a Neotropical savanna tree species that has high phenotypic plasticity. We obtained digital images of cross-sections of its leaves developed under different light conditions (sun vs. shade), different seasons (dry vs. wet) and in different soil types (oxysoil vs. hydromorphic soil), and analyzed several visual attributes, such as color, texture and tissues thickness in a perpendicular plane from microscopic images. The experimental results demonstrated that computational analysis is capable of distinguishing anatomical alterations in microscope images obtained from individuals growing in different environmental conditions. The methods presented here offer an alternative way to determine leaf anatomical differences. © 2013 Elsevier B.V.

Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees

Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V. All rights reserved.

The Brazilian version of the Neuropsychiatric Inventory-Clinician rating scale (NPI-C): Reliability and validity in dementia

ABSTRACT Background: Patients with dementia may be unable to describe their symptoms, and caregivers frequently suffer emotional burden that can interfere with judgment of the patient's behavior. The Neuropsychiatric Inventory-Clinician rating scale (NPI-C) was therefore developed as a comprehensive and versatile instrument to assess and accurately measure neuropsychiatric symptoms (NPS) in dementia, thereby using information from caregiver and patient interviews, and any other relevant available data. The present study is a follow-up to the original, cross-national NPI-C validation, evaluating the reliability and concurrent validity of the NPI-C in quantifying psychopathological symptoms in dementia in a large Brazilian cohort. Methods: Two blinded raters evaluated 312 participants (156 patient-knowledgeable informant dyads) using the NPI-C for a total of 624 observations in five Brazilian centers. Inter-rater reliability was determined through intraclass correlation coefficients for the NPI-C domains and the traditional NPI. Convergent validity included correlations of specific domains of the NPI-C with the Brief Psychiatric Rating Scale (BPRS), the Cohen-Mansfield Agitation Index (CMAI), the Cornell Scale for Depression in Dementia (CSDD), and the Apathy Inventory (AI). Results: Inter-rater reliability was strong for all NPI-C domains. There were high correlations between NPI-C/delusions and BPRS, NPI-C/apathy-indifference with the AI, NPI-C/depression-dysphoria with the CSDD, NPI-C/agitation with the CMAI, and NPI-C/aggression with the CMAI. There was moderate correlation between the NPI-C/aberrant vocalizations and CMAI and the NPI-C/hallucinations with the BPRS. Conclusion: The NPI-C is a comprehensive tool that provides accurate measurement of NPS in dementia with high concurrent validity and inter-rater reliability in the Brazilian setting. In addition to universal assessment, the NPI-C can be completed by individual domains. © International Psychogeriatric Association 2013.

Calling behavior and parasite intensity in Treefrogs, Hypsiboas prasinus

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genealogia e biopoder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudio económico de América Latina y el Caribe, 1987: síntesis preliminar = Economic survey of Latin America and the Caribbean, 1987: advance summary

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Políticas de financiamiento de las empresas de menor tamaño: experiencias recientes en América Latina

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