Transient stability analysis of electric energy systems via a fuzzy ART-ARTMAP neural network

This work presents a methodology to analyze transient stability (first oscillation) of electric energy systems, using a neural network based on ART architecture (adaptive resonance theory), named fuzzy ART-ARTMAP neural network for real time applications. The security margin is used as a stability analysis criterion, considering three-phase short circuit faults with a transmission line outage. The neural network operation consists of two fundamental phases: the training and the analysis. The training phase needs a great quantity of processing for the realization, while the analysis phase is effectuated almost without computation effort. This is, therefore the principal purpose to use neural networks for solving complex problems that need fast solutions, as the applications in real time. The ART neural networks have as primordial characteristics the plasticity and the stability, which are essential qualities to the training execution and to an efficient analysis. The fuzzy ART-ARTMAP neural network is proposed seeking a superior performance, in terms of precision and speed, when compared to conventional ARTMAP, and much more when compared to the neural networks that use the training by backpropagation algorithm, which is a benchmark in neural network area. (c) 2005 Elsevier B.V. All rights reserved.

Neural network based on adaptive resonance theory with continuous training for multi-configuration transient stability analysis of electric power systems

This work presents a methodology to analyze electric power systems transient stability for first swing using a neural network based on adaptive resonance theory (ART) architecture, called Euclidean ARTMAP neural network. The ART architectures present plasticity and stability characteristics, which are very important for the training and to execute the analysis in a fast way. The Euclidean ARTMAP version provides more accurate and faster solutions, when compared to the fuzzy ARTMAP configuration. Three steps are necessary for the network working, training, analysis and continuous training. The training step requires much effort (processing) while the analysis is effectuated almost without computational effort. The proposed network allows approaching several topologies of the electric system at the same time; therefore it is an alternative for real time transient stability of electric power systems. To illustrate the proposed neural network an application is presented for a multi-machine electric power systems composed of 10 synchronous machines, 45 buses and 73 transmission lines. (C) 2010 Elsevier B.V. All rights reserved.

Stability analysis of power systems described with detailed models by automatic method

The power system stability analysis is approached taking into explicit account the dynamic performance of generators internal voltages and control devices. The proposed method is not a direct method in the usual sense since conclusion for stability or instability is not exclusively based on energy function considerations but it is automatic since the conclusion is achieved without an analyst intervention. The stability test accounts for the nonconservative nature of the system with control devices such as the automatic voltage regulator (AVR) and automatic generation control (AGC) in contrast with the well-known direct methods. An energy function is derived for the system with machines forth-order model, AVR and AGC and it is used to start the analysis procedure and to point out criticalities. The conclusive analysis itself is made by means of a method based on the definition of a region surrounding the equilibrium point where the system net torque is equilibrium restorative. This region is named positive synchronization region (PSR). Since the definition of the PSR boundaries have no dependence on modelling approximation, the PSR test conduces to reliable results. (C) 2008 Elsevier Ltd. All rights reserved.

Multidimensional cluster stability analysis from a Brazilian Bradyrhizobium sp RFLP/PCR data set

The taxonomy of the N(2)-fixing bacteria belonging to the genus Bradyrhizobium is still poorly refined, mainly due to conflicting results obtained by the analysis of the phenotypic and genotypic properties. This paper presents an application of a method aiming at the identification of possible new clusters within a Brazilian collection of 119 Bradryrhizobium strains showing phenotypic characteristics of B. japonicum and B. elkanii. The stability was studied as a function of the number of restriction enzymes used in the RFLP-PCR analysis of three ribosomal regions with three restriction enzymes per region. The method proposed here uses Clustering algorithms with distances calculated by average-linkage clustering. Introducing perturbations using sub-sampling techniques makes the stability analysis. The method showed efficacy in the grouping of the species B. japonicum and B. elkanii. Furthermore, two new clusters were clearly defined, indicating possible new species, and sub-clusters within each detected cluster. (C) 2008 Elsevier B.V. All rights reserved.

Stability analysis of the D-dimensional nonlinear Schrodinger equation with trap and two- and three-body interactions

Considering the static solutions of the D-dimensional nonlinear Schrodinger equation with trap and attractive two-body interactions, the existence of stable solutions is limited to a maximum critical number of particles, when D greater than or equal to 2. In case D = 2, we compare the variational approach with the exact numerical calculations. We show that, the addition of a positive three-body interaction allows stable solutions beyond the critical number. In this case, we also introduce a dynamical analysis of the conditions for the collapse. (C) 2000 Published by Elsevier B.V. B.V. All rights reserved.

Designing spatial correlation of quantum dots: towards self-assembled three-dimensional structures

Buried two-dimensional arrays of InP dots were used as a template for the lateral ordering of self-assembled quantum dots. The template strain field can laterally organize compressive (InAs) as well as tensile (GaP) self-assembled nanostructures in a highly ordered square lattice. High-resolution transmission electron microscopy measurements show that the InAs dots are vertically correlated to the InP template, while the GaP dots are vertically anti-correlated, nucleating in the position between two buried InP dots. Finite InP dot size effects are observed to originate InAs clustering but do not affect GaP dot nucleation. The possibility of bilayer formation with different vertical correlations suggests a new path for obtaining three-dimensional pseudocrystals.

Micellar modification of drug stability: analysis of the effect of hexadecyltrimethylammonium halides on the rate of degradation of cephaclor

The intra- and intermolecular rates of degradation of cephaclor were determined with and without hexadecyltrimethylammonium bromide (CTABr). Micellar-derived spectral shifts were used to measure the association of the ionic forms as well as to determine the effect of CTABr on the apparent acid dissociation constant of the antibiotic. The rate of degradation of cephaclor increased with detergent and was salt sensitive. Micellar effects were analyzed quantitatively within the frame-work of the speudophase ion exchange model. All experimental data were fitted to this model which was used to predict the combined effects of pH and detergent concentration. Micelles increased the rate of OH- attack on cephaclor; most of the effect was due to the concentration of reagents in the micellar pseudophase. The intramolecular degradation was catalyzed 25-fold by micelles, and a working hypothesis to rationalize this effect is proposed. The results demonstrate that quantitative analysis can be utilized to assess and predict effects of detergents on drug stability.

Electric power systems transient stability analysis by neural networks

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Transient stability analysis of electrical power systems using a neural network based on fuzzy ARTMAP

This work presents a methodology to analyze transient stability for electric energy systems using artificial neural networks based on fuzzy ARTMAP architecture. This architecture seeks exploring similarity with computational concepts on fuzzy set theory and ART (Adaptive Resonance Theory) neural network. The ART architectures show plasticity and stability characteristics, which are essential qualities to provide the training and to execute the analysis. Therefore, it is used a very fast training, when compared to the conventional backpropagation algorithm formulation. Consequently, the analysis becomes more competitive, compared to the principal methods found in the specialized literature. Results considering a system composed of 45 buses, 72 transmission lines and 10 synchronous machines are presented. © 2003 IEEE.

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.

The importance of hormone receptor analysis in osteosarcoma cells growth submitted to treatment with estrogen in association with thyroid hormone

Bone tumor incidence in women peaks at age 50-60, coinciding with the menopause. That estrogen (E2) and triiodothyronine (T3) interact in bone metabolism has been well established. However, few data on the action of these hormones are available. Our purpose was to determine the role of E2 and T3 in the expression of bone activity markers, namely alkaline phosphatase (AP) and receptor activator of nuclear factor κB ligand (RANKL). Two osteosarcoma cell lines: MG-63 (which has both estrogen (ER) and thyroid hormone (TR) receptors) and SaOs-29 (ER receptors only) were treated with infraphysiological E2 associated with T3 at infraphysiological, physiological, and supraphysiological concentrations. Real-time RT-PCR was used for expression analysis. Our results show that, in MG-63 cells, infraphysiological E2 associated with supraphysiological T3 increases AP expression and decreases RANKL expression, while infraphysiological E2 associated with either physiological or supraphysiological T3 decreases both AP and RANKL expression. On the other hand, in SaOs-2 cells, the same hormone combinations had no significant effect on the markers' expression. Thus, the analysis of hormone receptors was shown to be crucial for the assessment of tumor potential growth in the face of hormonal changes. Special care should be provided to patients with T3 and E2 hormone receptors that may increase tumor growth. Copyright © 2007 John Wiley & Sons, Ltd.

Thermoelectric effects in quantum dots

We report a numerical renormalization-group study of the thermoelectric effect in the single-electron transistor (SET) and side-coupled geometries. As expected, the computed thermal conductance and thermopower curves show signatures of the Kondo effect and of Fano interference. The thermopower curves are also affected by particle-hole asymmetry. © 2009 Elsevier B.V. All rights reserved.

Electrogravimetric Analysis by Quartz-Crystal Microbalance on the Consumption of the Neurotransmitter Acetylcholine by Acetylcholinesterase

Electrogravimetric analysis was performed on the consumption of the neurotransmitter Acetylcholine (ACh) by Acetylcholinesterase (AChE) in situ and in real time. Michaelis-Menten assumption was achieved by using an enzyme micro-reactor in which the total enzyme was anchored in a quartz crystal microbalance chip (QCM-chip) with a strategically engineered self-assembled monolayer (SAM) of alkanethiols, which can prevent diffusion-controlled or spatially restricted kinetics. The real-time frequency changes indicated the rate of the products formation from enzymatic reaction. The QCM-chip was tested showing that it could demonstrate AChE inhibition by physostigmine. © 2013 Copyright Taylor and Francis Group, LLC.

The use of Gramian matrices for aeroelastic stability analysis

Most of the established procedures for analysis of aeroelastic flutter in the development of aircraft are based on frequency domain methods. Proposing new methodologies in this field is always a challenge, because the new methods need to be validated by many experimental procedures. With the interest for new flight control systems and nonlinear behavior of aeroelastic structures, other strategies may be necessary to complete the analysis of such systems. If the aeroelastic model can be written in time domain, using state-space formulation, for instance, then many of the tools used in stability analysis of dynamic systems may be used to help providing an insight into the aeroelastic phenomenon. In this respect, this paper presents a discussion on the use of Gramian matrices to determine conditions of aeroelastic flutter. The main goal of this work is to introduce how observability gramian matrix can be used to identify the system instability. To explain the approach, the theory is outlined and simulations are carried out on two benchmark problems. Results are compared with classical methods to validate the approach and a reduction of computational time is obtained for the second example. © 2013 Douglas Domingues Bueno et al.