303 resultados para INTENSIVE GLUCOSE CONTROL
Resumo:
The excess of sugarcane bagasse (SCB) from the sugar-alcohol industry is considered a by-product with great potential for many bioproducts production. This work had as objective to verify the performance of sugarcane bagasse hemicellulosic hydrolysate (SCBHH) as source of sugars for enzymatic or in vitro xylitol production. For this purpose, xylitol enzymatic production was evaluated using different concentrations of treated SCBHH in the commercial reaction media. The weak acid hydrolysis of SCB provided a hydrolysate with 18 g L(-1) and 6 g L(-1) of xylose and glucose, respectively. Considering the reactions, changes at xylose xylitol conversion efficiency and volumetric productivity in xylitol were not observed for the control experiment and using 20 and 40% v.v (1) of SCBHH in the reaction media. The conversion efficiency achieved 100% in all the experiments tested. The results showed that treated SCBHH is suitable as xylose and glucose source for the enzymatic xylitol production and that this process has potential as an alternative for traditional xylitol production ways. (C) 2011 Published by Elsevier Ltd.
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The objective of this research was to improve Glucose-6-phosphate dehydrogenase (G6PD) production by Saccharomyces cerevisiae W303-181, which carry the plasmid YEpPGK-G6PD, by varying the following cultivation conditions: pH value (4.8, 5.7 and 6.6); inoculum concentration (0.1, 0.6 and 1.1 g/L) and initial glucose concentration (20.0, 30.0 and 40.0 g/L). The effect of those variables on G6PD production capability was studied by the application of response surface statistical analysis. The results showed that the highest G6PD production (1594.2 U/L), specific activity (1189.7 U/g(cell)) and productivity (45.6 U/L.h) occurred at pH 4.8, inoculum concentration of 0.1 g/L and initial glucose concentration of 20.0 g/L, under agitation of 150 rpm at 30 degrees C after 36 h. In this work, the strain expressed about 21 fold more activity than the wild S. cerevisiae strain, being an attractive and promising new source of this enzyme.
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Purpose Adverse drug events (ADEs) are harmful and occur with alarming frequency in critically ill patients. Complex pharmacotherapy with multiple medications increases the probability of a drug interaction (DI) and ADEs in patients in intensive care units (ICUs). The objective of the study is to determine the frequency of ADEs among patients in the ICU of a university hospital and the drugs implicated. Also, factors associated with ADEs are investigated. Methods This cross-sectional study investigated 299 medical records of patients hospitalized for 5 or more days in an ICU. ADEs were identified through intensive monitoring adopted in hospital pharmacovigilance and also ADE triggers. Adverse drug reactions (ADR) causality was classified using the Naranjo algorithm. Data were analyzed through descriptive analysis, and through univariate and multiple logistic regression. Results The most frequent ADEs were ADRs type A, of possible causality and moderate severity. The most frequent ADR was drug-induced acute kidney injury. Patients with ADEs related to DIs corresponded to 7% of the sample. The multiple logistic regression showed that length of hospitalization (OR = 1.06) and administration of cardiovascular drugs (OR = 2.2) were associated with the occurrence of ADEs. Conclusion Adverse drug reactions of clinical significance were the most frequent ADEs in the ICU studied, which reduces patient safety. The number of ADEs related to drug interactions was small, suggesting that clinical manifestations of drug interactions that harm patients are not frequent in ICUs.
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Objective To evaluate drug interaction software programs and determine their accuracy in identifying drug-drug interactions that may occur in intensive care units. Setting The study was developed in Brazil. Method Drug interaction software programs were identified through a bibliographic search in PUBMED and in LILACS (database related to the health sciences published in Latin American and Caribbean countries). The programs` sensitivity, specificity, and positive and negative predictive values were determined to assess their accuracy in detecting drug-drug interactions. The accuracy of the software programs identified was determined using 100 clinically important interactions and 100 clinically unimportant ones. Stockley`s Drug Interactions 8th edition was employed as the gold standard in the identification of drug-drug interaction. Main outcome Sensitivity, specificity, positive and negative predictive values. Results The programs studied were: Drug Interaction Checker (DIC), Drug-Reax (DR), and Lexi-Interact (LI). DR displayed the highest sensitivity (0.88) and DIC showed the lowest (0.69). A close similarity was observed among the programs regarding specificity (0.88-0.92) and positive predictive values (0.88-0.89). The DIC had the lowest negative predictive value (0.75) and DR the highest (0.91). Conclusion The DR and LI programs displayed appropriate sensitivity and specificity for identifying drug-drug interactions of interest in intensive care units. Drug interaction software programs help pharmacists and health care teams in the prevention and recognition of drug-drug interactions and optimize safety and quality of care delivered in intensive care units.
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The standards in this chapter focus on maximising the patient`s ability to adhere to the treatment prescribed. Many people are extremely shocked when they are told they have TB, some refuse to accept it and others are relieved to find out what is wrong and that treatment is available. The reaction depends on many factors, including cultural beliefs and values, previous experience and knowledge of the disease. Even though TB is more common among vulnerable groups, it can affect anyone and it is important for patients to be able to discuss their concerns in relation to their own individual context. The cure for TB relies on the patient receiving a full, uninterrupted course of treatment, which can only be achieved if the patient and the health service work together. A system needs to be in place to trace patients who miss their appointments for treatment (late patients). The best success will be achieved through the use of flexible, innovative and individualised approaches. The treatment and care the patient has received will inevitably have an impact on his or her willingness to attend in the future. A well-defined system of late patient tracing is mandatory in all situations. However, when the rates are high (above 10%), any tracing system will be useless without also examining the service as a whole.
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SETTING: Thirty-six priority cities in Sao Paulo State, Brazil, with a high incidence of tuberculosis (TB) cases, deaths and treatment default. OBJECTIVE: To identify the perspectives of city TB control coordinators regarding the most important components of adherence strategies adopted by health care teams to ensure patient adherence in 36 priority cities in the State of Sao Paulo, Brazil. DESIGN: Qualitative research with semi-structured interviews conducted with the coordinators of the National TB Control Programme involved in the management of TB treatment services in the public sector. RESULTS: The main issues thought to influence adherence to directly observed treatment (DOT) by coordinators include incentives and benefits delivered to patients, patient-health care worker bonding and comprehensive care, the encouragement given by others to follow treatment (family, neighbours and health professionals), and help provided by health professionals for patients to recover their self-esteem. CONCLUSION: The main aspects mentioned by city TB control coordinators regarding patient adherence to treatment and to DOT in Sao Paulo are improvements in communications, relationships based on trust, a humane approach and including the patients in the decision-making process concerning their health.
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This paper presents a compact embedded fuzzy system for three-phase induction-motor scalar speed control. The control strategy consists in keeping constant the voltage-frequency ratio of the induction-motor supply source. A fuzzy-control system is built on a digital signal processor, which uses speed error and speed-error variation to change both the fundamental voltage amplitude and frequency of a sinusoidal pulsewidth modulation inverter. An alternative optimized method for embedded fuzzy-system design is also proposed. The controller performance, in relation to reference and load-torque variations, is evaluated by experimental results. A comparative analysis with conventional proportional-integral controller is also achieved.
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This paper presents a robust voltage control scheme for fixed-speed wind generators using a static synchronous compensator (STATCOM) controller. To enable a linear and robust control framework with structured uncertainty, the overall system is represented by a linear part plus a nonlinear part that covers an operating range of interest required to ensure stability during severe low voltages. The proposed methodology is flexible and readily applicable to larger wind farms of different configurations. The performance of the control strategy is demonstrated on a two area test system. Large disturbance simulations demonstrate that the proposed controller enhances voltage stability as well as transient stability of induction generators during low voltage ride through (LVRT) transients and thus enhances the LVRT capability. (C) 2011 Elsevier Ltd. All rights reserved.
Resumo:
We proposed a connection admission control (CAC) to monitor the traffic in a multi-rate WDM optical network. The CAC searches for the shortest path connecting source and destination nodes, assigns wavelengths with enough bandwidth to serve the requests, supervises the traffic in the most required nodes, and if needed activates a reserved wavelength to release bandwidth according to traffic demand. We used a scale-free network topology, which includes highly connected nodes ( hubs), to enhance the monitoring procedure. Numerical results obtained from computational simulations show improved network performance evaluated in terms of blocking probability.
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Two different fuzzy approaches to voltage control in electric power distribution systems are introduced in this paper. The real-time controller in each case would act on power transformers equipped with under-load tap changers. Learning systems are employed to turn the voltage-control relays into adaptive devices. The scope of this study has been limited to the power distribution substation, and the voltage measurements and control actions are carried out on the secondary bus. The capacity of fuzzy systems to handle approximate data, together with their unique ability to interpret qualitative information, make it possible to design voltage-control strategies that satisfy the requirements of the Brazilian regulatory bodies and the real concerns of the electric power distribution companies. Fuzzy control systems based on these two strategies have been implemented and the test results were highly satisfactory.
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A fuzzy control strategy for voltage regulation in electric power distribution systems is introduced in this article. This real-time controller would act on power transformers equipped with under-load tap changers. The fuzzy system was employed to turn the voltage-control relays into adaptive devices. The scope of the present study has been limited to the power distribution substation, and both the voltage measurements and control actions are carried out on the secondary bus. The capacity of fuzzy systems to handle approximate data, together with their unique ability to interpret qualitative information, make it possible to design voltage control strategies that satisfy both the requirements of the Brazilian regulatory bodies and the real concerns of the electric power distribution companies. A prototype based on the fuzzy control strategy proposed in this paper has also been implemented for validation purposes and its experimental results were highly satisfactory.
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This paper proposes an approach of optimal sensitivity applied in the tertiary loop of the automatic generation control. The approach is based on the theorem of non-linear perturbation. From an optimal operation point obtained by an optimal power flow a new optimal operation point is directly determined after a perturbation, i.e., without the necessity of an iterative process. This new optimal operation point satisfies the constraints of the problem for small perturbation in the loads. The participation factors and the voltage set point of the automatic voltage regulators (AVR) of the generators are determined by the technique of optimal sensitivity, considering the effects of the active power losses minimization and the network constraints. The participation factors and voltage set point of the generators are supplied directly to a computational program of dynamic simulation of the automatic generation control, named by power sensitivity mode. Test results are presented to show the good performance of this approach. (C) 2008 Elsevier B.V. All rights reserved.
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This paper presents a novel adaptive control scheme. with improved convergence rate, for the equalization of harmonic disturbances such as engine noise. First, modifications for improving convergence speed of the standard filtered-X LMS control are described. Equalization capabilities are then implemented, allowing the independent tuning of harmonics. Eventually, by providing the desired order vs. engine speed profiles, the pursued sound quality attributes can be achieved. The proposed control scheme is first demonstrated with a simple secondary path model and, then, experimentally validated with the aid of a vehicle mockup which is excited with engine noise. The engine excitation is provided by a real-time sound quality equivalent engine simulator. Stationary and transient engine excitations are used to assess the control performance. The results reveal that the proposed controller is capable of large order-level reductions (up to 30 dB) for stationary excitation, which allows a comfortable margin for equalization. The same holds for slow run-ups ( > 15s) thanks to the improved convergence rate. This margin, however, gets narrower with shorter run-ups (<= 10s). (c) 2010 Elsevier Ltd. All rights reserved.
Resumo:
In this paper, nonlinear dynamic equations of a wheeled mobile robot are described in the state-space form where the parameters are part of the state (angular velocities of the wheels). This representation, known as quasi-linear parameter varying, is useful for control designs based on nonlinear H(infinity) approaches. Two nonlinear H(infinity) controllers that guarantee induced L(2)-norm, between input (disturbances) and output signals, bounded by an attenuation level gamma, are used to control a wheeled mobile robot. These controllers are solved via linear matrix inequalities and algebraic Riccati equation. Experimental results are presented, with a comparative study among these robust control strategies and the standard computed torque, plus proportional-derivative, controller.
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This paper develops H(infinity) control designs based on neural networks for fully actuated and underactuated cooperative manipulators. The neural networks proposed in this paper only adapt the uncertain dynamics of the robot manipulators. They work as a complement of the nominal model. The H(infinity) performance index includes the position errors as well the squeeze force errors between the manipulator end-effectors and the object, which represents a complete disturbance rejection scenario. For the underactuated case, the squeeze force control problem is more difficult to solve due to the loss of some degrees of manipulator actuation. Results obtained from an actual cooperative manipulator, which is able to work as a fully actuated and an underactuated manipulator, are presented. (C) 2008 Elsevier Ltd. All rights reserved.