Allosteric modulation of pyrophosphatase activity of rat osseous plate alkaline phosphatase by magnesium ions

Pyrophosphatase activity of rat osseous plate alkaline phosphatase was studied at different concentrations of calcium and magnesium ions. with the aim of characterizing the modulation of enzyme activity by these metals. In the absence of metal ions, the enzyme hydrolysed pyrophosphate following Michaelian kinetics with a specific activity of 36.7 U/mg and K-0.5 = 88 mu M. In the presence of low concentrations (0.1 mM) of magnesium (or calcium) ions, the enzyme also exhibited Michaclian kinetics for the hydrolysis of pyrophosphate, but a significant increase in specific activity (123 U/mg) was observed. K-m values remained almost unchanged. Quite different behavior occurred in the presence of 2 mM magnesium (or calcium) ions. In addition to low-affinity sites (K-0.5 = 40 and 90 mu M, for magnesium and calcium, respectively), high-affinity sites were also observed with K-0.5 values 100-fold lower. The high-affinity sites observed in the presence of calcium ions represented about 10% of those observed for magnesium ions. This was correlated with the fact that only magnesium ions triggered conformational changes yielding a fully active enzyme. These results suggested that the enzyme could hydrolyse pyrophosphate, even at physiological concentrations (4 mu M), since magnesium concentrations are high enough to trigger conformational changes increasing the enzyme activity. A model, suggesting the involvement of magnesium ions in the hydrolysis of pyrophosphate by rat osseous plate alkaline phosphatase is proposed. (C) 1998 Published by Elsevier B.V. Ltd. All rights reserved.

Analysis of cardiac autonomic modulation in obese and eutrophic children

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

Context-specific modulation of cocaine-induced locomotor sensitization and ERK and CREB phosphorylation in the rat nucleus accumbens

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modulation of macrophage cytokine profiles during solid tumor progression: susceptibility to Candida albicans infection

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

Enhancement of optical absorption by modulation of the oxygen flow of TiO2 films deposited by reactive sputtering

Oxygen-deficient TiO2 films with enhanced visible and near-infrared optical absorption have been deposited by reactive sputtering using a planar diode radio frequency magnetron configuration. It is observed that the increase in the absorption coefficient is more effective when the O-2 gas supply is periodically interrupted rather than by a decrease of the partial O-2 gas pressure in the deposition plasma. The optical absorption coefficient at 1.5 eV increases from about 1 x 10(2) cm(-1) to more than 4 x 10(3) cm(-1) as a result of the gas flow discontinuity. A red-shift of similar to 0.24 eV in the optical absorption edge is also observed. High resolution transmission electron microscopy with composition analysis shows that the films present a dense columnar morphology, with estimated mean column width of 40nm. Moreover, the interruptions of the O-2 gas flow do not produce detectable variations in the film composition along its growing direction. X-ray diffraction and micro-Raman experiments indicate the presence of the TiO2 anatase, rutile, and brookite phases. The anatase phase is dominant, with a slight increment of the rutile and brookite phases in films deposited under discontinued O-2 gas flow. The increase of optical absorption in the visible and near-infrared regions has been attributed to a high density of defects in the TiO2 films, which is consistent with density functional theory calculations that place oxygen-related vacancy states in the upper third of the optical bandgap. The electronic structure calculation results, along with the adopted deposition method and experimental data, have been used to propose a mechanism to explain the formation of the observed oxygen-related defects in TiO2 thin films. The observed increase in sub-bandgap absorption and the modeling of the corresponding changes in the electronic structure are potentially useful concerning the optimization of efficiency of the photocatalytic activity and the magnetic doping of TiO2 films. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4724334]

A novel neural model to electrical load forecasting in transformers

The paper describes a novel neural model to electrical load forecasting in transformers. The network acts as identifier of structural features to forecast process. So that output parameters can be estimated and generalized from an input parameter set. The model was trained and assessed through load data extracted from a Brazilian Electric Utility taking into account time, current, tension, active power in the three phases of the system. The results obtained in the simulations show that the developed technique can be used as an alternative tool to become more appropriate for planning of electric power systems.

An efficient neural approach to economic load dispatch in power systems

A neural approach to solve the problem defined by the economic load dispatch in power systems is presented in this paper, 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 nonlinear function makes them attractive for system optimization the neural networks applyed in economic load dispatch reported in literature sometimes fail to converge towards feasible equilibrium points the internal parameters of the modified Hopfield network developed here are computed using the valid-subspace technique These parameters guarantee the network convergence to feasible quilibrium points, A solution for the economic load dispatch problem corresponds to an equilibrium point of the network. Simulation results and comparative analysis in relation to other neural approaches are presented to illustrate efficiency of the proposed approach.

Neural Network-Based Approach for Identification of the Harmonic Content of a Nonlinear Load in a Single-Phase System

In this paper an alternative method based on artificial neural networks is presented to determine harmonic components in the load current of a single-phase electric power system with nonlinear loads, whose parameters can vary so much in reason of the loads characteristic behaviors as because of the human intervention. The first six components in the load current are determined using the information contained in the time-varying waveforms. The effectiveness of this method is verified by using it in a single-phase active power filter with selective compensation of the current drained by an AC controller. The proposed method is compared with the fast Fourier transform.

Effect of abutment's height and framework alloy on the load distribution of mandibular cantilevered implant-supported prosthesis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

An investigation of pile diameter influence in the bearing capacity on Dynamic Load Test (DLT)

During the construction of five residential buildings in the city of Taubate, State of São Paulo, it was possible to carry out one comprehensive investigation of the behavior of precast concrete piles in clay shales. This paper describes the results of Dynamic Load Tests (DLT's) executed in three piles with different diameters and with the same embedded length. The tests were monitored using the PDA(R) (Pile Driving Analyzer) and the pile top displacement was measured by pencil and paper procedure. From the curves of RMX versus DMX resulted from CASE(R) method, CAPWAPC(R) analyses were made for signals where the maximum mobilized soil resistance was verified. The results were compared with the predicted bearing capacity using the semi-empirical method of Decourt & Quaresma (1978) and Decourt (1982) based on SPT values and the description of the soil profile. Some comments related to the values of quake and damping used for clay shales in the analyses are also presented.

Experience gained and difficulties in performing dynamic load test in composite piles made with steel rails

The results of dynamic instrumentation in two construction sites that used steel rails as pile foundation are presented in this paper. The first dynamic load tests were executed in piles made by single steel rails of the type TR32 and TR37. In the second group of dynamic tests, the piles were made by a composition of two and three steel rails of the same type TR37. The difficulties in placing the sensors, the effect of hammer blow eccentricity and the influence of the non-uniform welding along the pile length are presented in detail and discussed.

Influences of thermal and electric load fluctuations in the cogeneration attractiveness

The use of mean values of thermal and electric demand can be justifiable for synthesising the configuration and for estimating the economic results because it simplifies the analysis in a preliminary feasibility study of a cogeneration plant. For determining the cogeneration scheme that best fits the energetic needs of a process several cycles and combinations must be considered, and those technically feasible will be analysed according to economic models. Although interesting for a first approach, this procedure do not consider that the peaks and valleys present in the load patterns will impose additional constraints relatively to the equipment capacities. In this paper, the effects of thermal and electric load fluctuation to the cogeneration plant design were considered. An approach for modelling these load variability is proposed for comparing two competing thermal and electric parity competing schemes. A gas turbine associated to a heat recovery steam generator was then proposed and analysed for thermal- and electric-following operational strategies. Thermal-following option revealed to be more attractive for the technical and economic limits defined for this analysis. (c) 2006 Elsevier Ltd. All rights reserved.

Describing fatigue crack growth and load ratio effects in Al 2524 T3 alloy with an enhanced exponential model

The fatigue crack behavior in metals and alloys under constant amplitude test conditions is usually described by relationships between the crack growth rate da/dN and the stress intensity factor range Delta K. In the present work, an enhanced two-parameter exponential equation of fatigue crack growth was introduced in order to describe sub-critical crack propagation behavior of Al 2524-T3 alloy, commonly used in aircraft engineering applications. It was demonstrated that besides adequately correlating the load ratio effects, the exponential model also accounts for the slight deviations from linearity shown by the experimental curves. A comparison with Elber, Kujawski and "Unified Approach" models allowed for verifying the better performance, when confronted to the other tested models, presented by the exponential model. (C) 2012 Elsevier Ltd. All rights reserved.

Load compensation in four-wire electrical power systems

This work describes a methodology for power factor control and correction of the unbalanced currents in four-wire electric circuits. The methodology is based on the insertion of two compensation networks, one wye-grounded neutral and another in delta, in parallel to the load. The mathematical development has been proposed in previous work [3]. In this paper, however, the methodology was adapted to accept different power factors for the system to be compensated. on the other hand, the determination of the compensation susceptances is based on the instantaneous values of the load currents. The results are obtained using the MatLab - Simulink environment.

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.