Variabilidade da frequência cardíaca como ferramenta de análise da função autonômica de tabagistas: revisão de literatura e estudo do plot de Poincaré

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Industrialization in Latin America: from the black box" to the "empty box": a comparison of contemporary industrialization patterns"

Includes bibliography

Previsão estocástica de nível fluviométrico para cidade de Marabá-PA: método de Box-Jenkins

O Município de Marabá- PA, situado na região Amazônica, sudeste do Estado do Pará, sofre anualmente com eventos de enchentes, ocasionados pelo aumento periódico do rio Tocantins e pela situação de vulnerabilidade da população que reside em áreas de risco. A defesa civil estadual e municipal anualmente planeja e prepara equipes para ações de defesa no município. Nesta fase o monitoramento e previsão de eventos de enchentes são importantes. Portanto, com o objetivo de diminuir erros nas previsões hidrológicas para o Município de Marabá, desenvolveu-se um modelo estocástico para previsão de nível do rio Tocantins, baseado na metodologia de Box e Jenkins. Utilizou os dados de níveis diários observados nas estações hidrológicas de Marabá e Carolina e Conceição do Araguaia da Agência Nacional de Águas (ANA), do período de 01/12/ 2008 a 31/03/2011. Efetuou-se o ajustamento de três modelos (M_t, N_t e Y_t), através de diferentes aplicativos estatísticos: o SAS e o Gretl, usando diferentes interpretações do comportamento das séries para gerar as equações dos modelos. A principal diferença entre os aplicativos é que no SAS usa o modelo de função de transferência na modelagem. Realizou-se uma classificação da variabilidade do nível do rio, através da técnica dos Quantis para o período de 1972 a 2011, examinando-se apenas as categorizações de níveis ACIMA e MUITO ACIMA do normal. Para análise de impactos socioeconômicos foram usados os dados das ações da Defesa Civil Estado do Pará nas cheias de 2009 e 2011. Os resultados mostraram que o número de eventos de cheias com níveis MUITO ACIMA do normal, geralmente, podem estar associados a eventos de La Niña. Outro resultado importante: os modelos gerados simularam muito bem o nível do rio para o período de sete dias (01/04/2011 a 07/04/2011). O modelo multivariado N_t (com pequenos erros) representou o comportamento da série original, subestimando os valores reais nos dias 3, 4 e 5 de abril de 2011, com erro máximo de 0,28 no dia 4. O modelo univariado (Y_t) teve bons resultados nas simulações com erros absolutos em torno de 0,12 m. O modelo com menor erro absoluto (0,08m) para o mesmo período foi o modelo M_t, desenvolvido pelo aplicativo SAS, que interpreta a série original como sendo não linear e não estacionária. A análise quantitativa dos impactos fluviométricos, ocorridos nas enchentes de 2009 e 2011 na cidade de Marabá, revelou em média que mais de 4 mil famílias sofrem com estes eventos, implicado em gastos financeiros elevados. Logo, conclui-se que os modelos de previsão de níveis são importantes ferramentas que a Defesa Civil, utiliza no planejamento e preparo de ações preventivas para o município de Marabá.

Previsão da velocidade dos ventos por redes neurais artificiais e arima de box & jenkins

Pós-graduação em Engenharia Elétrica - FEIS

microRNA156-targeted SPL/ SBP box transcription factors regulate tomato ovary and fruit development

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

Distribution and population structure of the flecked box crab Hepatus pudibundus (Decapoda, Brachyura) in the western South Atlantic

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

The bias in reversing the Box-Cox transformation in time series forecasting: An empirical study based on neural networks

The Box-Cox transformation is a technique mostly utilized to turn the probabilistic distribution of a time series data into approximately normal. And this helps statistical and neural models to perform more accurate forecastings. However, it introduces a bias when the reversion of the transformation is conducted with the predicted data. The statistical methods to perform a bias-free reversion require, necessarily, the assumption of Gaussianity of the transformed data distribution, which is a rare event in real-world time series. So, the aim of this study was to provide an effective method of removing the bias when the reversion of the Box-Cox transformation is executed. Thus, the developed method is based on a focused time lagged feedforward neural network, which does not require any assumption about the transformed data distribution. Therefore, to evaluate the performance of the proposed method, numerical simulations were conducted and the Mean Absolute Percentage Error, the Theil Inequality Index and the Signal-to-Noise ratio of 20-step-ahead forecasts of 40 time series were compared, and the results obtained indicate that the proposed reversion method is valid and justifies new studies. (C) 2014 Elsevier B.V. All rights reserved.

Avaliação in vitro da resistência adesiva ao cisalhamento entre a dentina bovina, cimentos resinosos e materiais restauradores indiretos, tratados ou não com jato de óxido de alumínio, ácido fluorídrico e silano

The purpose of this study was to evaluate in vitro the shear bond strenght to bovine dentin, during 24h and 30 days with the following variables: resin cements Enforce and Panavia F; aesthetics restorative materials Art Glass, IPS Empress 2 and Targis, with surface treatment with microetching with aluminium oxide, fluoridric acid and silane. Two hundred eighty eight sound bovine teeth from 3 years old animals constituted the samples after inclusion on polyester resin box. lnstron model 430 Universal Testing Machine, a crosshead speed 0,5 mm/min and load cells of 500 Kg, was used for shear bond strenght testing (MPa). The results were statistically analysed by ANOVA The best result was obtained with /PS Empress 2, microetched with aluminium oxide, fluoridric acid and silane, cemented with Panavia F and stored in distilled water, 3f'C during 30 days

Fractal scaling exponents of heart rate variability association with linear indices and Poincaré Plot

The literature indicated that the fractal analysis of heart rate variability (HRV) is related to the chaos theory. However, it is not clear if the both short and long-term fractal scaling exponents of HRV are reliable for short period analysis in women. We evaluated the association of the fractal exponents of HRV with the time and frequency domain and geometric indices of HRV. We evaluated 65 healthy women between 18 and 30 years old. HRV was analyzed with a minimal number of 256 RR intervals in the time (SDNN, RMSSD, NN50 and pNN50) and frequency (LF, HF and LF/HF ratio) domains, the geometric index were also analyzed (triangular indexRRtri, triangular interpolation of RR intervals-TINN and Poincaré plot-SD1, SD2 and SD1/SD2) as well as short and long-term fractal exponents (alpha-1 and alpha-2) of the detrended fluctuation analysis (DFA). No significant correlation was observed for alpha-2 exponent with all indices. There was significant correlation of the alpha-1 exponent with RMSSD, pNN50, SDNN/RMSSD, LF (nu), HF (nu and ms2 ), LF/HF ratio, SD1 and SD1/SD2 ratio. Our data does not indicate the alpha-2 exponent to be used for 256 RR intervals and we support the alpha-1 exponent to be used for HRV analysis in this condition.

Structure, diversity, and spatial patterns in a permanent plot of a high Restinga forest in Southeastern Brazil

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

Spatial methods for plot-based sampling of wildlife populations

Classical sampling methods can be used to estimate the mean of a finite or infinite population. Block kriging also estimates the mean, but of an infinite population in a continuous spatial domain. In this paper, I consider a finite population version of block kriging (FPBK) for plot-based sampling. The data are assumed to come from a spatial stochastic process. Minimizing mean-squared-prediction errors yields best linear unbiased predictions that are a finite population version of block kriging. FPBK has versions comparable to simple random sampling and stratified sampling, and includes the general linear model. This method has been tested for several years for moose surveys in Alaska, and an example is given where results are compared to stratified random sampling. In general, assuming a spatial model gives three main advantages over classical sampling: (1) FPBK is usually more precise than simple or stratified random sampling, (2) FPBK allows small area estimation, and (3) FPBK allows nonrandom sampling designs.

A Tool Box Half Full: How Social Science can Help Solve Human–Wildlife Conflict

There is a growing recognition among wildlife managers that focusing management on wildlife often provides a temporary fix to human–wildlife conflicts, whereas changing human behavior can provide long-term solutions. Human dimensions research of wildlife conflicts frequently focuses on stakeholders’ characteristics, problem identification, and acceptability of management, and less frequently on human behavior and evaluation of management actions to change that behavior. Consequently, little information exists to assess overall success of management. We draw on our experience studying human–bear conflicts, and argue for more human dimensions studies that focus on change in human behavior to measure management success. We call for help from social scientists to conduct applied experiments utilizing two methods, direct observation and self-reported data, to measure change in behavior. We are optimistic these approaches will help fill the managers’ tool box and lead to better integration of human dimensions into human–wildlife conflict management.

Two-chamber Rocket Box Bat House Plans

Plans and instructions for building a “Two-chamber Rocket Box” bat-house to accommodate large numbers (>200) of bats. See further: http://www.batcon.org/educatorsK/pdfs/fof_bathouse.pdf

Human telomere disease due to disruption of the CCAAT box of the TERC promoter

Mutations in the coding region of telomerase complex genes can result in accelerated telomere attrition and human disease. Manifestations of telomere disease include the bone marrow failure syndromes dyskeratosis congenita and aplastic anemia, acute myeloid leukemia, liver cirrhosis, and pulmonary fibrosis. Here, we describe a mutation in the CCAAT box (GCAAT) of the TERC gene promoter in a family in which multiple members had typical features of telomeropathy. The genetic alteration in this critical regulatory sequence resulted in reduced reporter gene activity and absent binding of transcription factor NF-Y, likely responsible for reduced TERC levels, decreased telomerase activity, and short telomeres. This is the first description of a pathogenic mutation in the highly con-served CCAAT box and the first instance of a mutation in the promoter region of TERC producing a telomeropathy. We propose that current mutation-screening strategies should include gene promoter regions for the diagnosis of telomere diseases. This clinical trial was registered at www.clinicaltrials.gov as #NCT00071045. (Blood. 2012;119(13):3060-3063)