967 resultados para Continuous use medicines


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The solar driven photo-Fenton process for treating water containing phenol as a contaminant has been evaluated by means of pilot-scale experiments with a parabolic trough solar reactor (PTR). The effects of Fe(II) (0.04-1.0 mmol L(-1)), H(2)O(2) (7-270 mmol L(-1)), initial phenol concentration (100 and 500 mg C L(-1)), solar radiation, and operation mode (batch and fed-batch) on the process efficiency were investigated. More than 90% of the dissolved organic carbon (DOC) was removed within 3 hours of irradiation or less, a performance equivalent to that of artificially-irradiated reactors, indicating that solar light can be used either as an effective complementary or as an alternative source of photons for the photo-Fenton degradation process. A non-linear multivariable model based on a neural network was fit to the experimental results of batch-mode experiments in order to evaluate the relative importance of the process variables considered on the DOC removal over the reaction time. This included solar radiation, which is not a controlled variable. The observed behavior of the system in batch-mode was compared with fed-batch experiments carried out under similar conditions. The main contribution of the study consists of the results from experiments under different conditions and the discussion of the system behavior. Both constitute important information for the design and scale-up of solar radiation-based photodegradation processes.

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Pipeline systems play a key role in the petroleum business. These operational systems provide connection between ports and/or oil fields and refineries (upstream), as well as between these and consumer markets (downstream). The purpose of this work is to propose a novel MINLP formulation based on a continuous time representation for the scheduling of multiproduct pipeline systems that must supply multiple consumer markets. Moreover, it also considers that the pipeline operates intermittently and that the pumping costs depend on the booster stations yield rates, which in turn may generate different flow rates. The proposed continuous time representation is compared with a previously developed discrete time representation [Rejowski, R., Jr., & Pinto, J. M. (2004). Efficient MILP formulations and valid cuts for multiproduct pipeline scheduling. Computers and Chemical Engineering, 28, 1511] in terms of solution quality and computational performance. The influence of the number of time intervals that represents the transfer operation is studied and several configurations for the booster stations are tested. Finally, the proposed formulation is applied to a larger case, in which several booster configurations with different numbers of stages are tested. (C) 2007 Elsevier Ltd. All rights reserved.

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In this paper the continuous Verhulst dynamic model is used to synthesize a new distributed power control algorithm (DPCA) for use in direct sequence code division multiple access (DS-CDMA) systems. The Verhulst model was initially designed to describe the population growth of biological species under food and physical space restrictions. The discretization of the corresponding differential equation is accomplished via the Euler numeric integration (ENI) method. Analytical convergence conditions for the proposed DPCA are also established. Several properties of the proposed recursive algorithm, such as Euclidean distance from optimum vector after convergence, convergence speed, normalized mean squared error (NSE), average power consumption per user, performance under dynamics channels, and implementation complexity aspects, are analyzed through simulations. The simulation results are compared with two other DPCAs: the classic algorithm derived by Foschini and Miljanic and the sigmoidal of Uykan and Koivo. Under estimated errors conditions, the proposed DPCA exhibits smaller discrepancy from the optimum power vector solution and better convergence (under fixed and adaptive convergence factor) than the classic and sigmoidal DPCAs. (C) 2010 Elsevier GmbH. All rights reserved.

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In this paper, we devise a separation principle for the finite horizon quadratic optimal control problem of continuous-time Markovian jump linear systems driven by a Wiener process and with partial observations. We assume that the output variable and the jump parameters are available to the controller. It is desired to design a dynamic Markovian jump controller such that the closed loop system minimizes the quadratic functional cost of the system over a finite horizon period of time. As in the case with no jumps, we show that an optimal controller can be obtained from two coupled Riccati differential equations, one associated to the optimal control problem when the state variable is available, and the other one associated to the optimal filtering problem. This is a separation principle for the finite horizon quadratic optimal control problem for continuous-time Markovian jump linear systems. For the case in which the matrices are all time-invariant we analyze the asymptotic behavior of the solution of the derived interconnected Riccati differential equations to the solution of the associated set of coupled algebraic Riccati equations as well as the mean square stabilizing property of this limiting solution. When there is only one mode of operation our results coincide with the traditional ones for the LQG control of continuous-time linear systems.

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The main goal of this paper is to apply the so-called policy iteration algorithm (PIA) for the long run average continuous control problem of piecewise deterministic Markov processes (PDMP`s) taking values in a general Borel space and with compact action space depending on the state variable. In order to do that we first derive some important properties for a pseudo-Poisson equation associated to the problem. In the sequence it is shown that the convergence of the PIA to a solution satisfying the optimality equation holds under some classical hypotheses and that this optimal solution yields to an optimal control strategy for the average control problem for the continuous-time PDMP in a feedback form.

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This work is concerned with the existence of an optimal control strategy for the long-run average continuous control problem of piecewise-deterministic Markov processes (PDMPs). In Costa and Dufour (2008), sufficient conditions were derived to ensure the existence of an optimal control by using the vanishing discount approach. These conditions were mainly expressed in terms of the relative difference of the alpha-discount value functions. The main goal of this paper is to derive tractable conditions directly related to the primitive data of the PDMP to ensure the existence of an optimal control. The present work can be seen as a continuation of the results derived in Costa and Dufour (2008). Our main assumptions are written in terms of some integro-differential inequalities related to the so-called expected growth condition, and geometric convergence of the post-jump location kernel associated to the PDMP. An example based on the capacity expansion problem is presented, illustrating the possible applications of the results developed in the paper.

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We consider in this paper the optimal stationary dynamic linear filtering problem for continuous-time linear systems subject to Markovian jumps in the parameters (LSMJP) and additive noise (Wiener process). It is assumed that only an output of the system is available and therefore the values of the jump parameter are not accessible. It is a well known fact that in this setting the optimal nonlinear filter is infinite dimensional, which makes the linear filtering a natural numerically, treatable choice. The goal is to design a dynamic linear filter such that the closed loop system is mean square stable and minimizes the stationary expected value of the mean square estimation error. It is shown that an explicit analytical solution to this optimal filtering problem is obtained from the stationary solution associated to a certain Riccati equation. It is also shown that the problem can be formulated using a linear matrix inequalities (LMI) approach, which can be extended to consider convex polytopic uncertainties on the parameters of the possible modes of operation of the system and on the transition rate matrix of the Markov process. As far as the authors are aware of this is the first time that this stationary filtering problem (exact and robust versions) for LSMJP with no knowledge of the Markov jump parameters is considered in the literature. Finally, we illustrate the results with an example.

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This paper deals with the expected discounted continuous control of piecewise deterministic Markov processes (PDMP`s) using a singular perturbation approach for dealing with rapidly oscillating parameters. The state space of the PDMP is written as the product of a finite set and a subset of the Euclidean space a""e (n) . The discrete part of the state, called the regime, characterizes the mode of operation of the physical system under consideration, and is supposed to have a fast (associated to a small parameter epsilon > 0) and a slow behavior. By using a similar approach as developed in Yin and Zhang (Continuous-Time Markov Chains and Applications: A Singular Perturbation Approach, Applications of Mathematics, vol. 37, Springer, New York, 1998, Chaps. 1 and 3) the idea in this paper is to reduce the number of regimes by considering an averaged model in which the regimes within the same class are aggregated through the quasi-stationary distribution so that the different states in this class are replaced by a single one. The main goal is to show that the value function of the control problem for the system driven by the perturbed Markov chain converges to the value function of this limit control problem as epsilon goes to zero. This convergence is obtained by, roughly speaking, showing that the infimum and supremum limits of the value functions satisfy two optimality inequalities as epsilon goes to zero. This enables us to show the result by invoking a uniqueness argument, without needing any kind of Lipschitz continuity condition.

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In this paper it is presented the theoretical background, the architecture (using the ""4+1"" model), and the use of the library for execution of adaptive devices, AdapLib. This library was created seeking to be accurate to the adaptive devices theory, and to allow its easy extension considering the specific details of solutions that employ this kind of device. As an example, it is presented a case study in which the library was used to create a proof of concept to monitor and diagnose problems in an online news portal.

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At present, the cement industry generates approximately 5% of the world`s anthropogenic CO(2) emissions. This share is expected to increase since demand for cement based products is forecast to multiply by a factor of 2.5 within the next 40 years and the traditional strategies to mitigate emissions, focused on the production of cement, will not be capable of compensating such growth. Therefore, additional mitigation strategies are needed, including an increase in the efficiency of cement use. This paper proposes indicators for measuring cement use efficiency, presents a benchmark based on literature data and discusses potential gains in efficiency. The binder intensity (bi) index measures the amount of binder (kg m(-3)) necessary to deliver 1 MPa of mechanical strength, and consequently express the efficiency of using binder materials. The CO(2) intensity index (ci) allows estimating the global warming potential of concrete formulations. Research benchmarks show that bi similar to 5 kg m(-3) MPa(-1) are feasible and have already been achieved for concretes >50 MPa. However, concretes with lower compressive strengths have binder intensities varying between 10 and 20 kg m(-3) MPa(-1). These values can be a result of the minimum cement content established in many standards and reveal a significant potential for performance gains. In addition, combinations of low bi and ci are shown to be feasible. (c) 2010 Elsevier Ltd. All rights reserved.

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This work presents a method for predicting resource availability in opportunistic grids by means of use pattern analysis (UPA), a technique based on non-supervised learning methods. This prediction method is based on the assumption of the existence of several classes of computational resource use patterns, which can be used to predict the resource availability. Trace-driven simulations validate this basic assumptions, which also provide the parameter settings for the accurate learning of resource use patterns. Experiments made with an implementation of the UPA method show the feasibility of its use in the scheduling of grid tasks with very little overhead. The experiments also demonstrate the method`s superiority over other predictive and non-predictive methods. An adaptative prediction method is suggested to deal with the lack of training data at initialization. Further adaptative behaviour is motivated by experiments which show that, in some special environments, reliable resource use patterns may not always be detected. Copyright (C) 2009 John Wiley & Sons, Ltd.

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Owing to its toxicity, aluminum (Al), which is one of the most abundant metals, inhibits the productivity of many cultures and affects the microbial metabolism. The aim of this work was to investigate the capacity of sugar cane vinasse to mitigate the adverse effects of Al on cell growth, viability, and budding, as the likely result of possible chelating action. For this purpose, Fleischmann`s yeast (Saccharomyces cerevisiae) was used in growth tests performed in 125-mL Erlenmeyer flasks containing 30 mL of YED medium (5.0 g/L yeast extract plus 20 g/L glucose) supplemented with the selected amounts of either vinasse or Al in the form of AlCl(3) center dot A H(2)O. Without vinasse, the addition of increasing levels of Al up to 54 mg/L reduced the specific growth rate by 18%, whereas no significant reduction was observed in its presence. The toxic effect of Al on S. cerevisiae growth and the mitigating effect of sugar cane vinasse were quantified by the exponential model of Ciftci et al. (Biotechnol Bioeng 25:2007-2023, 1983). The cell viability decreased from 97.7% at the start to 84.0% at the end of runs without vinasse and to 92.3% with vinasse. On the other hand, the cell budding increased from 7.62% at the start to 8.84% at the end of runs without vinasse and to 17.8% with vinasse. These results demonstrate the ability of this raw material to stimulate cell growth and mitigate the toxic effect of Al.

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The water-wind crisscross region of the Loess Plateau in China is comprised of 17.8 million hectares of highly erodible soil under limited annual rainfall. This requires a sustainable water balance for the restoration of dryland ecosystems to reduce and manage soil erosion. In this region, alfalfa has been one of the main legumes grown to minimize soil erosion. However, alfalfa yields were significantly lower in years of reduced rainfall suggesting that high water use and deep rooting alfalfa make it an unsustainable crop due to the long-term decline in soil water storage and productivity. Our objectives in this Study were to evaluate the soil water balance of Loess Plateau soils during vegetative restoration and to evaluate practices that prevent soil desiccation and promote ecosystem restoration and sustainability. Field observations of soil moisture recovery and soil erosion were carried out for five years after alfalfa was replaced with different crops and with bare soil. Soil water content changes in cropland, rangeland, and bare soil were tracked over several years, using a water balance approach. Results indicate that growing forages significantly reduced runoff and sediment transport. A forage-food-crop rotation is a better choice than other cropping systems for achieving sustainable productivity and preventing soil erosion and desiccation. However, economic considerations have prevented its widespread adoption by local farmers. Alternatively, this study recommends consideration of grassland crops or forest ecosystems to provide a sustainable water balance in the Loess Plateau of China. (C) 2009 Elsevier B.V. All rights reserved.

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Long-term vegetation restoration carried out on the slopes of the Loess Plateau of China employed different spatial and temporal land-use patterns but very little is known about the effects of these patterns on soil water-content variability. For this study the small Donggou catchment was selected to investigate soil water-content distributions for three spatial scales, including the entire catchment area, sampling transects, and land-use systems. Gravimetric soil water contents were determined incrementally to a soil depth of 1.20 m, on 10 occasions from April to October, 2007, at approximately 20-day intervals. Results indicated that soil water contents were affected by the six land-use types, resulting in four distinct patterns of vertical distribution of soil moisture (uniform, increasing, decreasing, and fluctuating with soil depth). The soil water content and its variation were also influenced in a complex manner by five land-use patterns distributed along transects following the gradients of five similar slopes. These patterns with contrasting hydrological responses in different components, such as forage land (alfalfa)-cropland-shrubland or shrubland-grassland (bunge needlegrass)-cropland-grassland, showed the highest soil water-content variability. Soil water at the catchment scale exhibited a moderate variability for each measurement date, and the variability of soil water content decreased exponentially with increasing soil water content. The minimum sample size for accurate data for use in a hydrological model for the catchment, for example, required many more samples for drier (69) than for wet (10) conditions. To enhance erosion and runoff control, this study suggested two strategies for land management: (i) to create a mosaic pattern by land-use arrangement that located units with higher infiltration capacities downslope from those with lower soil infiltrabilities; and (ii) raising the soil-infiltration capacity of units within the spatial mosaic pattern where possible.

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We give reasons why demographic parameters such as survival and reproduction rates are often modelled well in stochastic population simulation using beta distributions. In practice, it is frequently expected that these parameters will be correlated, for example with survival rates for all age classes tending to be high or low in the same year. We therefore discuss a method for producing correlated beta random variables by transforming correlated normal random variables, and show how it can be applied in practice by means of a simple example. We also note how the same approach can be used to produce correlated uniform triangular, and exponential random variables. (C) 2008 Elsevier B.V. All rights reserved.