Assessment of brachial plexus blockade in chickens by an axillary approach

Objective To assess the brachial plexus block in chickens by an axillary approach and using a peripheral nerve stimulator.Study design Prospective, randomized, double-blinded study.Animals Six, 84-week old, female chickens.Methods Midazolam (1 mg kg(-1)) and butorphanol (1 mg kg(-1)) were administered into the pectoralis muscle. Fifteen minutes later, the birds were positioned in lateral recumbency and following palpation of the anatomic landmarks, a catheter was inserted using an axillary approach to the brachial plexus. Lidocaine or bupivacaine (1 mL kg(-1)) was injected after plexus localization by the nerve stimulator. Sensory function was tested before and after blockade (carpus, radius/ulna, humerus and pectoralis muscle) in the blocked and unblocked wings. The latency to onset of motor and sensory block and the duration of sensory block were recorded. A Friedman nonparametric one-way repeated-measures ANOVA was used to compare scores from baseline values over time and to compare the differences between wings at each time point.Results A total of 18 blocks were performed with a success rate of 66.6% (12/18). The latency for motor block was 2.8 +/- 1.1 and 3.2 +/- 0.4 minutes for lidocaine and bupivacaine, respectively. The latencies for and durations of the sensory block were 6.0 +/- 2.5 and 64.0 +/- 18.0 and 7.8 +/- 5.8 and 91.6 +/- 61.7 minutes for lidocaine and bupivacaine, respectively. There was no statistical difference between these times for lidocaine or bupivacaine. Sensory function was not abolished in nonblocked wings.Conclusions and clinical relevance The brachial plexus block was an easy technique to perform but had a high failure rate. It might be useful for providing anesthesia or postoperative analgesia of the wing in chickens and exotic avian species that have similar wing anatomy.

A decentralized approach for optimal reactive power dispatch using a Lagrangian decomposition method

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Elicitation of multivariate prior distributions: A nonparametric Bayesian approach

In the context of Bayesian statistical analysis, elicitation is the process of formulating a prior density f(.) about one or more uncertain quantities to represent a person's knowledge and beliefs. Several different methods of eliciting prior distributions for one unknown parameter have been proposed. However, there are relatively few methods for specifying a multivariate prior distribution and most are just applicable to specific classes of problems and/or based on restrictive conditions, such as independence of variables. Besides, many of these procedures require the elicitation of variances and correlations, and sometimes elicitation of hyperparameters which are difficult for experts to specify in practice. Garthwaite et al. (2005) discuss the different methods proposed in the literature and the difficulties of eliciting multivariate prior distributions. We describe a flexible method of eliciting multivariate prior distributions applicable to a wide class of practical problems. Our approach does not assume a parametric form for the unknown prior density f(.), instead we use nonparametric Bayesian inference, modelling f(.) by a Gaussian process prior distribution. The expert is then asked to specify certain summaries of his/her distribution, such as the mean, mode, marginal quantiles and a small number of joint probabilities. The analyst receives that information, treating it as a data set D with which to update his/her prior beliefs to obtain the posterior distribution for f(.). Theoretical properties of joint and marginal priors are derived and numerical illustrations to demonstrate our approach are given. (C) 2010 Elsevier B.V. All rights reserved.

Sphere of influence and gravitational capture radius: a dynamical approach

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Comparative studies on non-convex optimization methods for transmission network expansion planning

We have investigated and extensively tested three families of non-convex optimization approaches for solving the transmission network expansion planning problem: simulated annealing (SA), genetic algorithms (GA), and tabu search algorithms (TS). The paper compares the main features of the three approaches and presents an integrated view of these methodologies. A hybrid approach is then proposed which presents performances which are far better than the ones obtained with any of these approaches individually. Results obtained in tests performed with large scale real-life networks are summarized.

Bayesian and multivariate methods applied to favorability quantification in recôncavo Basin and Ribeira Belt, Brazil

A methodology to define favorable areas in petroleum and mineral exploration is applied, which consists in weighting the exploratory variables, in order to characterize their importance as exploration guides. The exploration data are spatially integrated in the selected area to establish the association between variables and deposits, and the relationships among distribution, topology, and indicator pattern of all variables. Two methods of statistical analysis were compared. The first one is the Weights of Evidence Modeling, a conditional probability approach (Agterberg, 1989a), and the second one is the Principal Components Analysis (Pan, 1993). In the conditional method, the favorability estimation is based on the probability of deposit and variable joint occurrence, with the weights being defined as natural logarithms of likelihood ratios. In the multivariate analysis, the cells which contain deposits are selected as control cells and the weights are determined by eigendecomposition, being represented by the coefficients of the eigenvector related to the system's largest eigenvalue. The two techniques of weighting and complementary procedures were tested on two case studies: 1. Recôncavo Basin, Northeast Brazil (for Petroleum) and 2. Itaiacoca Formation of Ribeira Belt, Southeast Brazil (for Pb-Zn Mississippi Valley Type deposits). The applied methodology proved to be easy to use and of great assistance to predict the favorability in large areas, particularly in the initial phase of exploration programs. © 1998 International Association for Mathematical Geology.

Global optimization approach for the H2-norm model reduction problem

A branch and bound algorithm is proposed to solve the H2-norm model reduction problem for continuous-time linear systems, with conditions assuring convergence to the global optimum in finite time. The lower and upper bounds used in the optimization procedure are obtained through Linear Matrix Inequalities formulations. Examples illustrate the results.

Transient stability indices from a hybrid approach

This paper deals with hybrid method for transient stability analysis combining time domain simulation and a direct method. Nowadays, the step-by-step simulation is the best available tool for allowing the uses of detailed models and for providing reliable results. The main limitation of this approach involves the large time of computational simulations and the absence of stability margin. On the other hand, direct methods, that demand less CPU time, did not show ample reliability and applicability yet. The best way seems to be using hybrid solutions, in which a direct method is incorporated in a time domain simulation tool. This work has studied a direct method using the transient potential and kinetic energy of the critical machine only. In this paper the critical machine is identified by a fast and efficient method, and the proposal is new for using to get stability margins from hybrid approaches. Results from systems, like 16-machine, show stability indices to dynamic security assessment. © 2001 IEEE.

Natural fiber reinforced unsaturated polyester composites - An approach on compression molding

This work has been performed at Tapetes Sao Carlos-Brazil with the cooperation of the DaimlerChrysler Research Center Team in Ulm - Germany. The objective of the present paper is to report the results obtained with natural fiber reinforced unsaturated polyester (UP) composites, concerning surface quality measurements. The fibers that have been chosen for this work were sisal and curaua. The samples were produced by compression molding technique and afterwards submitted to three different tests, namely: a) thermal aging; b) water absorption and c) artificial weathering. The surface parameters measured before and after the tests were gloss, haze, short and long-waviness. The results have shown that after the tests there is a high loss of gloss, a high increase in haze, and a high increase in short and long-waviness as well. Curaua reinforced composites had a slightly better behavior when compared with sisal reinforced composites. The effect of the presence of filler and the addition of thermoplastic polyester (TP) on the material behavior has not been evidently detected. This result shows that the conventional technology/methods applied to UP-Fiberglass systems cannot be transferred to natural fibers without any modification. The fiber-matrix interaction and its response to the presence of additives must be fully understood before a successful processing route can be developed for painted natural fibers reinforced UP. Copyright © 2001 Society of Automotive Engineers, Inc.

The two-impurity Anderson model: An effective medium approach

The two-impurity Anderson model is solved within a effective medium approach. All impurity parameters are modelled via Slater atomic orbitals. Impurity spectral densities and spin correlation functions are readily computed. Results are presented for the zero temperature, half-filled case. © 2002 Elsevier Science B.V. All rights reserved.

A Bayesian approach for constructing genetic maps when markers are miscoded

The advent of molecular markers has created opportunities for a better understanding of quantitative inheritance and for developing novel strategies for genetic improvement of agricultural species, using information on quantitative trait loci (QTL). A QTL analysis relies on accurate genetic marker maps. At present, most statistical methods used for map construction ignore the fact that molecular data may be read with error. Often, however, there is ambiguity about some marker genotypes. A Bayesian MCMC approach for inferences about a genetic marker map when random miscoding of genotypes occurs is presented, and simulated and real data sets are analyzed. The results suggest that unless there is strong reason to believe that genotypes are ascertained without error, the proposed approach provides more reliable inference on the genetic map.

Clarke's alpha, beta and zero components: A possible approach for the conceptual design of instrumentation compatible with IEEE Std. 1459-2000

The paper explains the conceptual design of instrumentation that measures electric quantities defined in the trial-use Std. 1459-2000. It is shown how the Instantaneous-Space-Phasor (ISP) approach, based on α, β, 0 components, can be used to monitor electric energy flow, evaluate the utilization of transmission line and quantify the level of harmonic pollution injected by nonlinear loads.

Stability analysis of power system including facts (TCSC) effects by direct method approach

The problem of power system stability including the effects of a flexible alternating current transmission system (FACTS) is approached. First, the controlled series compensation is considered in the machine against infinite bar system and its effects are taken into account by means of construction of a Lyapunov function (LF). This simple system is helpful in order to understand the form the device affects dynamic and transient performance of the power system. After, the multimachine case is considered and it is shown that the single-machine results apply to multimachine systems. An energy-form Lyapunov function is derived for the power system including the FACTS device and it is used to analyse damping and synchronizing effects due to the FACTS device in single-machine as well as in multimachine power systems. © 2005 Elsevier Ltd. All rights reserved.

How the delphi and AHP methods are aiding to define the critical success factors priorities in a digital factory project implementation

Digital factory is a concept that offers a collaborative approach to enhance product and production engineering processes through simulation. Products, processes and resources are modeled to be used to develop and test the product conception and manufacturing processes, before their use in the real factory. The purpose of this paper is to present the steps to identify the Critical Success Factors (CSF) priorities in a digital factory project implementation in a Brazilian company and how the Delphi and AHP Methods are aiding to identify these CSF priorities. Copyright © 2008 SAE International.

A regularized nonlinear diffusion approach for texture image denoising

In this paper a new partial differential equation based method is presented with a view to denoising images having textures. The proposed model combines a nonlinear anisotropic diffusion filter with recent harmonic analysis techniques. A wave atom shrinkage allied to detection by gradient technique is used to guide the diffusion process so as to smooth and maintain essential image characteristics. Two forcing terms are used to maintain and improve edges, boundaries and oscillatory features of an image having irregular details and texture. Experimental results show the performance of our model for texture preserving denoising when compared to recent methods in literature. © 2009 IEEE.