Species richness of pteridophytes in a montane Atlantic rain forest plot of Southern Brazil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

BODE Index and GOLD Staging as Predictors of 1-Year Exacerbation Risk in Chronic Obstructive Pulmonary Disease

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

Effect of different plot coverings on emergence and early development of seven palm species (arecaceae)

The Arecaceae family comprises plants with economical importance in many Brazilian regions, for agricultural exploration or for landscaping. In great portion, species of this family present low germination velocity and percentage. This work meant to evaluate the germination and early development of seven palm species (Archontophoenix alexandrae H. Wendl. et Drude, Copernicia prunifera (Miller) H.E. Moore, Latania commersonii Gmel., Livistona chinensis R. Br., Syagrus campos-portoana Bondar, Syagrus coronata (Mart.) Beccari, Syagrus picrophylla Barb. Rod.), submitted to three kinds of seed bed plot coverings. Three 10 x 2 m seedbeds were built and filled with a mixture of sand, soil and chicken manure (1:3:0.5 proportion), where two lines were sown with each specie. On top of each seedbed, plastic covering and fifty percent screen were set allowing one third of the seedbed to full sunlight exposure. Seedbeds were irrigated by dripping system. All species had the same germination rate, regardless of the covering, by the end of the experiment (146 days after sowing), eventhough, A. alexandrae under plastic covering conditions, L. commersonii at full sunlight exposure and Syagrus campos-portoana under fifty percent shade, had reached that percentage around 51 days after sowing. The remaining species reached the greatest germination percentage earlier with some of the coverings, rather than at full sunlight exposure. For the studied conditions, covering type had no effect in leaf length and width. For leaf number, there was interaction between species x covering type for Livistona chinensis and Copernicia prunifera.

Poincaré plot indexes of heart rate variability: Relationships with other nonlinear variables

The Poincaré plot for heart rate variability analysis is a technique considered geometrical and non-linear, that can be used to assess the dynamics of heart rate variability by a representation of the values of each pair of R-R intervals into a simplified phase space that describes the system's evolution. The aim of the present study was to verify if there is some correlation between SD1, SD2 and SD1/SD2 ratio and heart rate variability nonlinear indexes either in disease or healthy conditions. 114 patients with arterial coronary disease and 65 healthy subjects underwent 30. minute heart rate registration, in supine position and the analyzed indexes were as follows: SD1, SD2, SD1/SD2, Sample Entropy, Lyapunov Exponent, Hurst Exponent, Correlation Dimension, Detrended Fluctuation Analysis, SDNN, RMSSD, LF, HF and LF/HF ratio. Correlation coefficients between SD1, SD2 and SD1/SD2 indexes and the other variables were tested by the Spearman rank correlation test and a regression analysis. We verified high correlation between SD1/SD2 index and HE and DFA (α1) in both groups, suggesting that this ratio can be used as a surrogate variable. © 2013 Elsevier B.V.

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)

Interpretação gravimétrica-magnética da zona de fratura dupla Bode Verde

Em Janeiro de 1980, foi realizada a Operação Bode Verde I do Projeto CENTRATLAN, que constou da coleta de dados geofísicos e geológicos na área central da Cadeia Mesoatlântica (CMA), a sul da Ilha de Ascensão. Esta operação fez parte de um convênio firmado entre a Marinha Americana e a Marinha Brasileira, cujo objetivo era investigar o Oceano Atlântico Sul, especialmente a área onde se estende a província fisiográfica da Cadeia Mesoatlântica. Com o objetivo de estudar a Zona de Fratura Dupla Bode Verde, e assim conhecer melhor esta feição tão marcante no fundo oceânico e margem continental, foram tratados e interpretados os dados batimétricos, gravimétricos e magnéticos colhidos na operação anteriormente citada. A análise dos dados batimétricos permitiu uma definição para esta zona de fratura, com o seu caráter duplo marcado pela presença de duas calhas contínuas, paralelas entre si, e separadas por um alto que tem o seu próprio "rift-valley". As anomalias gravimétricas encontradas confirmam o caráter duplo, com os dois mínimos observados correspondendo às duas calhas da fratura. Estas calhas separam um bloco crustal de aproximadamente 40 km de largura. Com base nos dados gravimétricos, foram construídas nove seções crustais sobre a zona de fratura, que permitiram observar que a interface crosta-manto sofre um afinamento crustal embaixo das paredes da fratura. Esta interface, que encontra-se normalmente a uma profundidade de 8-9 km, passa a atingir profundidades de 5.5-6.0 km abaixo das paredes da fratura, com a crosta apresentando uma espessura de 2.0 km nestas partes. Este afinamento crustal é causado pela subida de material do manto. A extensiva alteração hidrotermal que ocorre na depressão central da fratura, pode ser a responsável pelo menor afinamento crustal observado nesta parte da zona de fratura. Para a interpretação dos dados magnéticos, foi usada uma escala de tempo de polaridade magnética entre o Cretáceo Inferior e o Cenozóico, e uma taxa de espalhamento oceânico de 2.0 cm/ano. Para a camada de basalto, que é responsável por parte das anomalias magnéticas observadas, foi usada uma espessura média de 0.5 km. Nas paredes da zona de fratura, ocorre uma diminuição na espessura desta camada, havendo uma interrupção da mesma na depressão central da fratura.

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.