The Physiological, Enzymatic, and Genetic Characterization of Staphylococcus sp. Chromium (VI) Reductase Function

A strain of Staphylococcus isolated by Dr. Fekete at the Sandia National Laboratory toxic metal dumping site in Sandia, New Mexico. has been found to reduce toxic Cr(VI) to the less toxic Cr(IlI) state. We have ascertained the environmental parameters for optimal bacterial growth and Cr(VI) reduction. This knowledge may be employed in a comprehensive bioremediation scheme designed to accelerate natural reparation of that Sandia ecosystem. In addition we have investigated the genetic and enzymatic basis for this Cr(VI) reducing ability. This information may allow us to create more effective bioremediation schemes based on the comprehensive knowledge of enzyme and gene function. Preliminary investigations have been carried out toward this end which may serve as the basis for a more thorough investigation.

Use of social network analysis to indentify the coopetition in a commercial cluster plan

The cluster provides a greater commercial relationship between the companies that comprise it. This encourages companies to adopt competitive structures that allow solving problems that would hardly alone (Lubeck et. Al., 2011). With that this paper aims to describe the coopetition between companies operating on a commercial cluster planned, from the point of view of retailers, taking as a basis the theoretical models proposed by Bengtsson and Kock (1999) and Leon (2005) and operationalized by means of Social Network Analysis (SNA). Data collection consisted of two phases, the first exploratory aspect to identify the actors, and the second was characterized as descriptive as it aims to describe the coopetition among the enterprises. As a result we identified the companies that cooperate and compete simultaneously (coopetition), firms that only compete, companies just cooperate and businesses that do not compete and do not cooperate (coexistence)

Estimating the stochastic discount factor without a utility function

Using the Pricing Equation in a panel-data framework, we construct a novel consistent estimator of the stochastic discount factor (SDF) which relies on the fact that its logarithm is the serial-correlation ìcommon featureîin every asset return of the economy. Our estimator is a simple function of asset returns, does not depend on any parametric function representing preferences, is suitable for testing di§erent preference speciÖcations or investigating intertemporal substitution puzzles, and can be a basis to construct an estimator of the risk-free rate. For post-war data, our estimator is close to unity most of the time, yielding an average annual real discount rate of 2.46%. In formal testing, we cannot reject standard preference speciÖcations used in the literature and estimates of the relative risk-aversion coe¢ cient are between 1 and 2, and statistically equal to unity. Using our SDF estimator, we found little signs of the equity-premium puzzle for the U.S.

Precificação em orquestradores de informação: maximizando redes estáveis

Em redes de inovação baseadas em trocas de informação, o agente orquestrador se apropria das informações dos atores periféricos, gera inovação e distribui em forma de valor agregado. É sua função promover a estabilidade na rede fazendo com que a mesma tenha taxas não negativas de crescimento. Nos mercados de análise de crédito e fraude, por exemplo, ou bureaus funcionam como agentes orquestradores, concentrando as informações históricas da população que são provenientes de seus clientes e fornecendo produtos que auxiliam na tomada de decisão. Assumindo todas as empresas do ecossistema como agentes racionais, a teoria dos jogos se torna uma ferramenta apropriada para o estudo da precificação dos produtos como mecanismo de promoção da estabilidade da rede. Este trabalho busca identificar a relação de diferentes estruturas de precificação promovidas pelo agente orquestrador com a estabilidade e eficiência da rede de inovação. Uma vez que o poder da rede se dá pela força conjunta de seus membros, a inovação por esta gerada varia de acordo com a decisão isolada de cada agente periférico de contratar o agente orquestrador ao preço por ele estipulado. Através da definição de um jogo teórico simplificado onde diferentes agentes decidem conectar-se ou não à rede nas diferentes estruturas de preços estipuladas pelo agente orquestrador, o estudo analisa as condições de equilíbrio conclui que o equilíbrio de Nash implica em um cenário de estabilidade da rede. Uma conclusão é que, para maximizar o poder de inovação da rede, o preço a ser pago por cada agente para fazer uso da rede deve ser diretamente proporcional ao benefício financeiro auferido pela inovação gerada pela mesma. O estudo apresenta ainda uma simulação computacional de um mercado fictício para demonstração numérica dos efeitos observados. Através das conclusões obtidas, o trabalho cobre uma lacuna da literatura de redes de inovação com agentes orquestradores monopolistas em termos de precificação do uso da rede, servindo de subsídio de tomadores de decisão quando da oferta ou demanda dos serviços da rede.

Separação cega de fontes lineares e não lineares usando algoritmo genético, redes neurais artificiais RBF e negentropia de Rényi como medida de independência

Conventional methods to solve the problem of blind source separation nonlinear, in general, using series of restrictions to obtain the solution, often leading to an imperfect separation of the original sources and high computational cost. In this paper, we propose an alternative measure of independence based on information theory and uses the tools of artificial intelligence to solve problems of blind source separation linear and nonlinear later. In the linear model applies genetic algorithms and Rényi of negentropy as a measure of independence to find a separation matrix from linear mixtures of signals using linear form of waves, audio and images. A comparison with two types of algorithms for Independent Component Analysis widespread in the literature. Subsequently, we use the same measure of independence, as the cost function in the genetic algorithm to recover source signals were mixed by nonlinear functions from an artificial neural network of radial base type. Genetic algorithms are powerful tools for global search, and therefore well suited for use in problems of blind source separation. Tests and analysis are through computer simulations

Mathematical tests about the existence and applications of PPS-wavelets in function approximation problems

Neural networks and wavelet transform have been recently seen as attractive tools for developing eficient solutions for many real world problems in function approximation. Function approximation is a very important task in environments where computation has to be based on extracting information from data samples in real world processes. So, mathematical model is a very important tool to guarantee the development of the neural network area. In this article we will introduce one series of mathematical demonstrations that guarantee the wavelets properties for the PPS functions. As application, we will show the use of PPS-wavelets in pattern recognition problems of handwritten digit through function approximation techniques.

An efficient Hopfield network to solve economic dispatch problems with transmission system representation

Economic dispatch (ED) problems have recently been solved by artificial neural network approaches. Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. The ability of neural networks to realize some complex non-linear function makes them attractive for system optimization. All ED models solved by neural approaches described in the literature fail to represent the transmission system. Therefore, such procedures may calculate dispatch policies, which do not take into account important active power constraints. Another drawback pointed out in the literature is that some of the neural approaches fail to converge efficiently toward feasible equilibrium points. A modified Hopfield approach designed to solve ED problems with transmission system representation is presented in this paper. The transmission system is represented through linear load flow equations and constraints on active power flows. The internal parameters of such modified Hopfield networks are computed using the valid-subspace technique. These parameters guarantee the network convergence to feasible equilibrium points, which represent the solution for the ED problem. Simulation results and a sensitivity analysis involving IEEE 14-bus test system are presented to illustrate efficiency of the proposed approach. (C) 2004 Elsevier Ltd. All rights reserved.

Security constrained optimal active power flow via network model and interior point method

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Electrical load forecasting formulation by a fast neural network

The objective of this work is to develop a methodology for electric load forecasting based on a neural network. Here, backpropagation algorithm is used with an adaptive process that based on fuzzy logic and using a decaying exponential function to avoid instability in the convergence process. This methodology results in fast training, when compared to the conventional formulation of backpropagation algorithm. The results are presented using data from a Brazilian Electric Company, and shows a very good performance for the proposal objective.

An Efficient Codification to Solve Distribution Network Reconfiguration for Loss Reduction Problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Structural Basis of Importin-alpha-Mediated Nuclear Transport for Ku70 and Ku80

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Structural basis for metal ion coordination and the catalytic mechanism of sphingomyelinases D

Sphingomyelinases D (SMases D) from Loxosceles spider venom are the principal toxins responsible for the manifestation of dermonecrosis, intravascular hemolysis, and acute renal failure, which can result in death. These enzymes catalyze the hydrolysis of sphingomyelin, resulting in the formation of ceramide 1-phosphate and choline or the hydrolysis of lysophosphatidyl choline, generating the lipid mediator lysophosphatidic acid. This report represents the first crystal structure of a member of the sphingomyelinase D family from Loxosceles laeta (SMase I), which has been determined at 1.75-angstrom resolution using the quick cryo-soaking technique and phases obtained from a single iodine derivative and data collected from a conventional rotating anode x-ray source. SMase I folds as an (alpha/beta)(8) barrel, the interfacial and catalytic sites encompass hydrophobic loops and a negatively charged surface. Substrate binding and/or the transition state are stabilized by a Mg2+ ion, which is coordinated by Glu(32), Asp(34), Asp(91), and solvent molecules. In the proposed acid base catalytic mechanism, His(12) and His(47) play key roles and are supported by a network of hydrogen bonds between Asp(34), Asp(52), Trp(230), Asp(233), and Asn(252).

SMase II, a new sphingomyelinase D from Loxosceles laeta venom gland: Molecular cloning, expression, function and structural analysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Structural basis for branching-enzyme activity of glycoside hydrolase family 57: Structure and stability studies of a novel branching enzyme from the hyperthermophilic archaeon Thermococcus Kodakaraensis KOD1

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

On the Baker-Akhiezer function in the AKNS scheme

Expressions for the Baker-Akhiezer function and their logarithmic space and time derivatives are derived in terms of the matrix elements of U - V matrices and 'squared basis functions'. These expressions generalize the well known formulas for the KdV equation case and establish links between different forms of the Whitham averaging procedure.