Daniel G. Silva

The beta-3 adrenoceptor agonist, mirabegron relaxes isolated prostate from human and rabbit: new therapeutic indication?

Alpha1 (α1)‐blockers, 5‐alpha reductase and phosphodiesterase type‐5 inhibitors are pharmacological classes currently available for benign prostatic hyperplasia (BPH) treatment. Mirabegron, a beta‐3 adrenoceptor (β3‐AR) agonist has been approved for the therapy of overactive bladder and may constitute a new therapeutic option for BPH treatment. This study is aimed to evaluate the in vitro effects of mirabegron in human and rabbit prostatic smooth muscle.

An immune-inspired information-theoretic approach to the problem of ICA over a Galois field

The problem of independent component analysis (ICA) was firstly formulated and studied in the context of real-valued signals and mixing models, but, recently, an extension of this original formulation was proposed to deal with the problem within the framework of finite fields. In this work, we propose a strategy to deal with ICA over these fields that presents two novel features: (i) it is based on the use of a cost function built directly from an estimate of the mutual information and (ii) it employs an artificial immune system to perform the search for efficient separating matrices, in contrast with the existing techniques, which are based on search schemes of an exhaustive character. The new proposal is subject to a comparative analysis based on different simulation scenarios and the work is concluded by an analysis of perspectives of practical application to digital and genomic data mining.

Machine Learning Methods and Asymmetric Cost Function to Estimate Execution Effort of Software Testing

Planning and scheduling of testing activities play an important role for any independent test team that performs tests for different software systems, developed by different development teams. This work studies the application of machine learning tools and variable selection tools to solve the problem of estimating the execution effort of functional tests. An analysis of the test execution process is developed and experiments are performed on two real databases. The main contributions of this paper are the approach of selecting the significant variables for database synthesis and the use of an artificial neural network trained with an asymmetric cost function.

A Simple Approach for Estimation of Execution Effort of Functional Test Cases

Planning and scheduling of testing activities play a key-role for any independent test team that performs tests for different software systems, pertaining to different development teams. Based on the work experience with several software systems within the scope of one real-world project, we propose an alternative approach that focuses on team efficiency to estimate the execution effort of a test case suite. To assess the validity of the approach data collected on test activity along one year were used. The approach is simpler to use than current methods, requiring less effort to apply; furthermore, it can provide the test team good estimates even using a small amount of data.

Blind separation of convolutive mixtures over Galois fields

The efforts of Yeredor, Gutch, Gruber and Theis have established a theory of blind source separation (BSS) over finite fields that can be applied to linear and instantaneous mixing models. In this work, the problem is treated for the case of convolutive mixtures, for which the process of BSS must be understood in terms of space-time processing. A method based on minimum entropy and deflation is proposed, and structural conditions for perfect signal recovery are defined, establishing interesting points of contact with canonical MIMO equalization. Simulation results give support to the applicability of the proposed algorithm and also reveal the important role of efficient entropy estimation when the complexity of the mixing system is increased.

Fast communication: The modified MEXICO for ICA over finite fields

In 2007, a theory of ICA over finite fields emerged and an algorithm based on pairwise comparison of mixtures, called MEXICO, was developed to deal with this new problem. In this letter, we propose improvements in the method that, according to simulations in GF(2) and GF(3) scenarios, lead to a faster convergence and better separation results, increasing the application possibilities of the new theory in the context of large databases.

An immune-inspired, information-theoretic framework for blind inversion of Wiener systems

This work proposes a new approach to the blind inversion of Wiener systems. A Wiener system is composed of a linear time-invariant (LTI) sub-system followed by a memoryless nonlinear function. The goal is to recover the input signal by knowing just the output of the Wiener system, and the straightforward scheme to achieve this is called the Hammerstein system - apply a memoryless nonlinear mapping followed by a LTI sub-system to the output signal of the Wiener system. If the input of the Wiener system is originally iid and some mild conditions are satisfied, the inversion is possible. Based on this statement and the limitations of relevant previous works, a solution is proposed combining (i) immune-inspired optimization algorithms, (ii) information theory and (iii) IIR filters that yield a robust scheme with a relatively reduced risk of local convergence. Experimental results indicated a similar or superior performance of the new approach, in comparison with two other blind methodologies. HighlightsThis work proposes an immune-inspired algorithm to perform blind inversion of Wiener systems.The method employs mutual information-based criteria and IIR filters to adapt the inverse structure.The experimental results indicate a superior or equivalent performance of the new technique, in comparison with gradient-based search or kurtosis-based criterion.

A modified version of the MEXICO algorithm for performing ICA over Galois fields

The theory of ICA over finite fields, established in the last five years, gave rise to a corpus of different separation strategies, which includes an algorithm based on the pairwise comparison of mixtures, called MEXICO. In this work, we propose an alternative version of the MEXICO algorithm, with modifications that - as shown by the results obtained for a number of representative scenarios - lead to performance improvements in terms of the computational effort required to reach a certain performance level, especially for an elevated number of sources. This parsimony can be relevant to enhance the applicability of the new ICA theory to data mining in the context of large discrete-valued databases.

Laparoscopy Assisted Versus Open Ileocystoplasty in Pigs

PURPOSE We compared laparoscopy assisted and open ileocystoplasty in an experimental model in pigs. We evaluated intraoperative aspects, postoperative recovery, peritoneal adhesions and functional results. MATERIALS AND METHODS The study included 30 male pigs divided into 4 groups, including 10 with laparoscopy assisted ileocystoplasty, 10 with open surgery, 5 with sham laparoscopy and 5 with sham open surgery. Variables studied were total operative time, ileovesical anastomosis time, postoperative urodynamic findings (bladder capacity and compliance), daily and weekly weight gain, and intraperitoneal adhesions (incidence, type and score). RESULTS Mean operative time in the laparoscopic and open groups was 179.4 and 69.6 minutes, respectively, which was significantly different (p <0.05). Mean ileovesical anastomosis time was also significantly different for laparoscopic vs open surgery (74.8 vs 31.8 minutes, p <0.05). Significant differences were observed in mean weekly weight gain during the first 4 weeks after surgery. Postoperatively bladder capacity and compliance differences among the groups were not significantly different (p >0.05). The overall incidence of intraperitoneal adhesions was not significantly different in all groups (p >0.05). However, in the open vs laparoscopy, sham laparoscopy and sham open surgery groups adhesion complexity was greater and mean score was higher (4.2 vs 2.8, 2.0 and 2.0, respectively), which was statistically significantly different (p <0.05). CONCLUSIONS Laparoscopy assisted ileocystoplasty requires more operative time than open surgery. However, postoperative recovery is more rapid and intraperitoneal adhesions are less complex in pigs with laparoscopy assisted ileocystoplasty vs conventional surgery. Functional results are comparable for open and laparoscopy assisted ileocystoplasty.

Metaheuristics in Telecommunication Systems: Network Design, Routing, and Allocation Problems

Recent advances in the telecommunication industry offer great opportunities to citizens and organizations in a globally connected world, but they also arise a vast number of complex challenges that decision makers must face. Some of these challenges can be modeled as combinatorial optimization problems (COPs). Frequently, these COPs are large-size, NP-hard, and must be solved in “real time,” which makes necessary the use of metaheuristics. The first goal of this paper is to provide a review on how metaheuristics have been used so far to deal with COPs associated with telecommunication systems, detecting the main trends and challenges. Particularly, the analysis focuses on the network design, routing, and allocation problems. In addition, due to the nature of these challenges, the paper discusses how the hybridization of metaheuristics with methodologies such as simulation and machine learning can be employed to extend the capabilities of metaheuristics when solving stochastic and dynamic COPs in the telecommunication industry.