STUDY OF THE EQUATORIAL ATLANTIC OCEAN MIXING LAYER USING A ONE-DIMENSIONAL TURBULENCE MODEL

The General Ocean Turbulence Model (GOTM) is applied to the diagnostic turbulence field of the mixing layer (ML) over the equatorial region of the Atlantic Ocean. Two situations were investigated: rainy and dry seasons, defined, respectively, by the presence of the intertropical convergence zone and by its northward displacement. Simulations were carried out using data from a PIRATA buoy located on the equator at 23 degrees W to compute surface turbulent fluxes and from the NASA/GEWEX Surface Radiation Budget Project to close the surface radiation balance. A data assimilation scheme was used as a surrogate for the physical effects not present in the one-dimensional model. In the rainy season, results show that the ML is shallower due to the weaker surface stress and stronger stable stratification; the maximum ML depth reached during this season is around 15 m, with an averaged diurnal variation of 7 m depth. In the dry season, the stronger surface stress and the enhanced surface heat balance components enable higher mechanical production of turbulent kinetic energy and, at night, the buoyancy acts also enhancing turbulence in the first meters of depth, characterizing a deeper ML, reaching around 60 m and presenting an average diurnal variation of 30 m.

Consistency in approximate entropy given by a volumetric estimate

Non-linear methods for estimating variability in time-series are currently of widespread use. Among such methods are approximate entropy (ApEn) and sample approximate entropy (SampEn). The applicability of ApEn and SampEn in analyzing data is evident and their use is increasing. However, consistency is a point of concern in these tools, i.e., the classification of the temporal organization of a data set might indicate a relative less ordered series in relation to another when the opposite is true. As highlighted by their proponents themselves, ApEn and SampEn might present incorrect results due to this lack of consistency. In this study, we present a method which gains consistency by using ApEn repeatedly in a wide range of combinations of window lengths and matching error tolerance. The tool is called volumetric approximate entropy, vApEn. We analyze nine artificially generated prototypical time-series with different degrees of temporal order (combinations of sine waves, logistic maps with different control parameter values, random noises). While ApEn/SampEn clearly fail to consistently identify the temporal order of the sequences, vApEn correctly do. In order to validate the tool we performed shuffled and surrogate data analysis. Statistical analysis confirmed the consistency of the method. (C) 2008 Elsevier Ltd. All rights reserved.

Taxon surrogates among Amazonian mammals: Can total species richness be predicted by single orders?

Limited financial sources and the difficulty in performing complete surveys, allied to the speed of habitat fragmentation and the urgent necessity in select conservation areas, create the necessity of using some methodologies which bypass these problems. One possibility is the use of surrogate taxa that might be used as indicator of others groups richness and even total richness of an area. We investigated if the use of surrogate taxon is useful among seven mammal orders in Amazon. We tested through Pearson`s correlation (Bonferroni`s adjusted) if (1) there was a correlation between richness of total species and some order; (2) there was a significant pair wise correlation between species richness of each order; and (3) the combination of two orders would give better results as a surrogate for the total richness. The correlations found, in general, were positive. It means that the increase in the richness of an order was followed by its increase in another order, as well as in the total species richness. Only Didelphimorphia was significantly correlated with the total species richness. In the pair wise analyses only one assembly, Primates and Artiodactyla, was significantly correlated with total richness. Since indicator species are more effective within taxonomic groups (life-history characteristics are likely to be more different among than within major taxonomic groups), we suggest that an indicator group might be chosen for each one. In this case, for mammals from Amazon, it would be Didelphimorphia. (C) 2008 Elsevier Ltd. All rights reserved.

Functional and morphologic evaluation of kidney proximal tubuli and correlation with renal allograft prognosis

P>Renal transplant patients with stable graft function and proximal tubular dysfunction (PTD) have an increased risk for chronic allograft nephropathy (CAN). In this study, we investigated the histologic pattern associated with PTD and its correlation with graft outcome. Forty-nine transplant patients with stable graft function were submitted to a biopsy. Simultaneously, urinary retinol-binding protein (uRBP) was measured and creatinine clearance was also determined. Banff`s score and semi-quantitative histologic analyses were performed to assess tubulointerstitial alterations. Patients were followed for 24.0 +/- 7.8 months. At biopsy time, mean serum creatinine was 1.43 +/- 0.33 mg/dl. Twelve patients (24.5%) had uRBP >= 1 mg/l, indicating PTD and 67% of biopsies had some degree of tubulointerstitial injury. At the end of the study period, 18 (36.7%) patients had lost renal function. uRBP levels were not associated with morphologic findings of interstitial fibrosis and tubular atrophy (IF/TA), interstitial fibrosis measured by Sirius red or tubulointerstitial damage. However, in multivariate analysis, the only variable associated with the loss of renal function was uRBP level >= 1 mg/l, determining a risk of 5.290 of loss of renal function (P = 0.003). Renal transplant patients who present PTD have functional alteration, which is not associated with morphologic alteration. This functional alteration is associated to progressive decrease in renal function.

Measurement error models with a general class of error distribution

In general, the normal distribution is assumed for the surrogate of the true covariates in the classical error model. This paper considers a class of distributions, which includes the normal one, for the variables subject to error. An estimation approach yielding consistent estimators is developed and simulation studies reported.