Rodrigo Cabral Farias

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trans-Dehydrocrotonin (t-DCTN), a 19-nor-clerodane diterpene isolated from the bark of Croton cajucara Benth. (Euphorbiaceae) demonstrated a significant hypoglycemic activity in alloxan-induced diabetic rats but not in normal rats, at oral doses of 25 and 50 mg/kg body weight. The drug also effectively lowered the blood sugar levels in glucose fed normal(More)
In signal processing, tensor decompositions have gained in popularity this last decade. In the meantime, the volume of data to be processed has drastically increased. This calls for novel methods to handle Big Data tensors. Since most of these huge data are issued from physical measurements, which are intrinsically real nonnegative, being able to compress(More)
Phytochemical and pharmacological studies of Croton cajucara were oriented by traditional medicine. The stem bark of the mature plant is a rich source of clerodane-type diterpenes: trans-dehydrocrotonin (DCTN), trans-crotonin (CTN), cis-cajucarin B, cajucarin A, cajucarinolide and two novel clerodanes, trans-cajucarin B and sacacarin. In young(More)
In this paper, adaptive estimation based on noisy quantized observations is studied. A low complexity adaptive algorithm using a quantizer with adjustable input gain and offset is presented. Three possible scalar models for the parameter to be estimated are considered: constant, Wiener process and Wiener process with deterministic drift. After showing that(More)
A Bayesian framework is proposed to define flexible coupling models for joint decompositions of data sets. Under this framework, a solution to the joint decomposition can be cast in terms of a maximum a posteriori estimator. Examples of joint posterior distributions are provided, including general Gaussian priors and non Gaussian coupling priors. Then(More)
A Bayesian framework is proposed to define flexible coupling models for joint tensor decompositions of multiple datasets. Under this framework, a natural formulation of the data fusion problem is to cast it in terms of a joint maximum a posteriori (MAP) estimator. Data-driven scenarios of joint posterior distributions are provided, including general(More)
In this paper, the asymptotic approximation of the Fisher information for the estimation of a scalar parameter based on quantized measurements is studied. As the number of quantization intervals tends to infinity, it is shown that the loss of Fisher information due to quantization decreases exponentially as a function of the number of quantization bits. The(More)
Estimation of a location parameter based on noisy and binary quantized measurements is considered in this letter. We study the behavior of the Cramér-Rao bound as a function of the quantizer threshold for different symmetric unimodal noise distributions. We show that, in some cases, the intuitive choice of threshold position given by the symmetry of(More)
In this paper, we study an asymptotic approximation of the Fisher information for the estimation of a scalar parameter using quantized measurements. We show that, as the number of quantization intervals tends to infinity, the loss of Fisher information induced by quantization decreases exponentially as a function of the number of quantization bits. A(More)