Optimal reactive power flow via the modified barrier Lagrangian function approach

A new approach called the Modified Barrier Lagrangian Function (MBLF) to solve the Optimal Reactive Power Flow problem is presented. In this approach, the inequality constraints are treated by the Modified Barrier Function (MBF) method, which has a finite convergence property: i.e. the optimal solution in the MBF method can actually be in the bound of the feasible set. Hence, the inequality constraints can be precisely equal to zero. Another property of the MBF method is that the barrier parameter does not need to be driven to zero to attain the solution. Therefore, the conditioning of the involved Hessian matrix is greatly enhanced. In order to show this, a comparative analysis of the numeric conditioning of the Hessian matrix of the MBLF approach, by the decomposition in singular values, is carried out. The feasibility of the proposed approach is also demonstrated with comparative tests to Interior Point Method (IPM) using various IEEE test systems and two networks derived from Brazilian generation/transmission system. The results show that the MBLF method is computationally more attractive than the IPM in terms of speed, number of iterations and numerical conditioning. (C) 2011 Elsevier B.V. All rights reserved.

Use of rhBMP-2 to reconstruct a severely atrophic mandible: a modified approach

This study reports the case of a patient with a severely resorbed mandible who was treated without a bone graft, using short implants, internal rigid fixation, rhBMP-2 and beta-tricalcium phosphate. A 76-year-old woman, with a severely resorbed mandible (less than 3 mm), reported a history of nearly 25 years of complete edentulism and consecutive treatment failures, with total bilateral exposed inferior alveolar nerves and complete bone resorption of the inferior border in some areas. The treatment of choice was the placement of a 2.0 mm thick unilock bone plate (MatrixMandible, Synthes Maxillofacial, Paoli, PA, USA), to reinforce the mandible. Eight short implants with a regular platform (Nobel Biocare, Goteborg, Sweden) were placed: three on the external oblique line on both sides and two on the symphysis. In order to augment mandible height and coat the exposed thread of the anterior implants, rhBMP-2 (Infuse Bone, Meditronic Sofamor Danek, Memphis, TN, USA) and beta-tricalcium phosphate (Cerasorb; Curasan, Kleinostheim, Germany) were used. Four 1.3 mm L miniplates were placed to support the graft. 14 months after surgery, the patient was satisfied and had excellent function without complications.

Introduction to the Software-defined Radio Approach

Telecommunications have been in constant evolution during past decades. Among the technological innovations, the use of digital technologies is very relevant. Digital communication systems have proven their efficiency and brought a new element in the chain of signal transmitting and receiving, the digital processor. This device offers to new radio equipments the flexibility of a programmable system. Nowadays, the behavior of a communication system can be modified by simply changing its software. This gave rising to a new radio model called Software Defined Radio (or Software-Defined Radio - SDR). In this new model, one moves to the software the task to set radio behavior, leaving to hardware only the implementation of RF front-end. Thus, the radio is no longer static, defined by their circuits and becomes a dynamic element, which may change their operating characteristics, such as bandwidth, modulation, coding rate, even modified during runtime according to software configuration. This article aims to present the use of GNU Radio software, an open-source solution for SDR specific applications, as a tool for development configurable digital radio.

A property rights approach to strategy

This article is about how resources can be conceptualized as bundles of attributes for which one can assign economic property rights. Strategic considerations are deliberately incorporated into the analysis through the assessment of the activities of capture and protection of property rights, along with the examination of the institutional environment. These basic elements combine in order to design an approach to strategy. In developing this approach, the authors identify four key questions for structuring the strategy formulation process of the firm. The analytical framework is illustrated through a particular case: the collection of royalties on the genetically modified (GM) technology in soybean seeds.

Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.

An anatomical analysis of the mini-modified orbitozygomatic and supra-orbital approaches

Seven sides of cadaver heads were used to compare the surgical exposures provided by the mini-modified orbitozygomatic (MOz) and supra-orbital (SO) approaches. The Optotrak 3020 computerized tracking system (Northern Digital, Waterloo, ON, Canada) was utilized to evaluate the area of anatomical exposure defined by six points: (1) ipsilateral sphenoid ridge; (2) most distal point of the ipsilateral middle cerebral artery (MCA); (3) most distal point of the ipsilateral posterior cerebral artery (PCA); (4) most distal point of the contralateral PCA; (5) most distal point of the contralateral MCA; and (6) contralateral sphenoid ridge. Additionally, angles of approach for the ipsilateral MCA bifurcation, ipsilateral ICA bifurcation, basilar artery tip, contralateral MCA and ICA bifurcation and anterior communicating artery (AcomA) were evaluated, first for SO and then for MOz. An image guidance system was used to evaluate the limits of surgical exposure. No differences in the area of surgical exposure were noted (p > 0.05). Vertical angles were significantly wider for the ipsilateral and contralateral ICA bifurcation, AcomA, contralateral MCA and basilar tip (p < 0.05) for MOz. No differences in horizontal angles were observed between the approaches for the six targets (p > 0.05). There were no differences in the limits of exposure. MOz affords no additional surgical working space. However, our results demonstrate systematically that vertical exposure is improved. The MOz should be performed while planning an approach to these regions and a wider exposure in the vertical axis is needed. (C) 2012 Elsevier Ltd. All rights reserved.

A Bayesian Approach for Decision Making on the Identification of Genes with Different Expression Levels: An Application to Escherichia coli Bacterium Data

A common interest in gene expression data analysis is to identify from a large pool of candidate genes the genes that present significant changes in expression levels between a treatment and a control biological condition. Usually, it is done using a statistic value and a cutoff value that are used to separate the genes differentially and nondifferentially expressed. In this paper, we propose a Bayesian approach to identify genes differentially expressed calculating sequentially credibility intervals from predictive densities which are constructed using the sampled mean treatment effect from all genes in study excluding the treatment effect of genes previously identified with statistical evidence for difference. We compare our Bayesian approach with the standard ones based on the use of the t-test and modified t-tests via a simulation study, using small sample sizes which are common in gene expression data analysis. Results obtained report evidence that the proposed approach performs better than standard ones, especially for cases with mean differences and increases in treatment variance in relation to control variance. We also apply the methodologies to a well-known publicly available data set on Escherichia coli bacterium.