Degradation of Poly(ethylene glycol) in Aqueous Solution by Photo-Fenton and H(2)O(2)/UV Processes

This article reports experimental results obtained in a laboratory-scale photochemical reactor on the photodegradation of poly(ethylene glycol) (PEG) in aqueous solutions by means of the photo-Fenton and H(2)O(2)/UV processes. Dilute water solutions of PEG were fed to a batch reactor, mixed with pertinent reactants, and allowed to react under different conditions. Reaction progress was evaluated by sampling and analyzing the concentration of the total organic carbon (TOC) in solution as a function of the reaction time. Organic acids formed during oxidation were determined by HPLC analyses. The main acids detected in both processes were acetic and formic. Glycolic acid was detected only in the photo-Fenton process, and malonic acid was detected only in the H(2)O(2)/UV treatment, indicating that different reaction paths occur in these processes. The characteristics of both processes are discussed, based on the evolution of the TOC-time curves and the concentration profiles of the monitored organic acids. The experimental results constitute a contribution to the design of industrial processes for the treatment of wastewaters containing soluble polymers with similar properties.

Treatment of Aqueous Effluents Containing Phenol by the O(3), O(3)-UV, and O(3)-H(2)O(2) Processes: Experimental Study and Neural Network Modeling

In this work, the oxidation of the model pollutant phenol has been studied by means of the O(3), O(3)-UV, and O(3)-H(2)O(2) processes. Experiments were carried out in a fed-batch system to investigate the effects of initial dissolved organic carbon concentration, initial, ozone concentration in the gas phase, the presence or absence of UVC radiation, and initial hydrogen peroxide concentration. Experimental results were used in the modeling of the degradation processes by neural networks in order to simulate DOC-time profiles and evaluate the relative importance of process variables.

Investigation of the mass transfer processes during the desalination of water containing phenol and sodium chloride by electrodialysis

Oxidation processes are used in wastewater treatment when conventional processes are not effective due to the presence of recalcitrant organic contaminants, like phenol. However, the presence of ionic compounds associated with organic pollutants may retard the oxidation. In this work the transport of species contained in an aqueous solution of phenol containing sodium chloride was evaluated in an electrodialysis (ED) system. An experimental study was carried out in which the influence of the process variables on the phenol loss and sodium chloride removal was investigated. Experiments were also performed without current, in order to determine the phenol transfer due to diffusion. The phenol and salt concentration variations in the ED compartments were measured over time, using dedicated procedures and an experimental design to determine the global characteristic parameters. A phenomenological approach was used to relate the phenol, salt and water fluxes with the driving forces (concentration and electric potential gradients). Under ED conditions, two contributions were pointed out for the phenol transport, i.e. diffusion and convection, this latter coming from the water flux due to electroosmosis related to the migration of salts. The fitting of the parameters of the transport equations resulted in good agreement with the experimental results over the range of conditions investigated. (c) 2008 Elsevier B.V. All rights reserved.

USE OF SOLAR ENERGY IN THE TREATMENT OF WATER CONTAMINATED WITH PHENOL BY PHOTOCHEMICAL PROCESSES

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.

The Policy Iteration Algorithm for Average Continuous Control of Piecewise Deterministic Markov Processes

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.

Generation of self-similar Gaussian time series by means of the DWT and DWPT variance maps

Due to the several kinds of services that use the Internet and data networks infra-structures, the present networks are characterized by the diversity of types of traffic that have statistical properties as complex temporal correlation and non-gaussian distribution. The networks complex temporal correlation may be characterized by the Short Range Dependence (SRD) and the Long Range Dependence - (LRD). Models as the fGN (Fractional Gaussian Noise) may capture the LRD but not the SRD. This work presents two methods for traffic generation that synthesize approximate realizations of the self-similar fGN with SRD random process. The first one employs the IDWT (Inverse Discrete Wavelet Transform) and the second the IDWPT (Inverse Discrete Wavelet Packet Transform). It has been developed the variance map concept that allows to associate the LRD and SRD behaviors directly to the wavelet transform coefficients. The developed methods are extremely flexible and allow the generation of Gaussian time series with complex statistical behaviors.

THE VANISHING DISCOUNT APPROACH FOR THE AVERAGE CONTINUOUS CONTROL OF PIECEWISE DETERMINISTIC MARKOV PROCESSES

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.

The collision branching process

We consider a branching model, which we call the collision branching process (CBP), that accounts for the effect of collisions, or interactions, between particles or individuals. We establish that there is a unique CBP, and derive necessary and sufficient conditions for it to be nonexplosive. We review results on extinction probabilities, and obtain explicit expressions for the probability of explosion and the expected hitting times. The upwardly skip-free case is studied in some detail.

Quasistationarity of continuous-time Markov chains with positive drift

We shall study continuous-time Markov chains on the nonnegative integers which are both irreducible and transient, and which exhibit discernible stationarity before drift to infinity sets in. We will show how this 'quasi' stationary behaviour can be modelled using a limiting conditional distribution: specifically, the limiting state probabilities conditional on not having left 0 for the last time. By way of a dual chain, obtained by killing the original process on last exit from 0, we invoke the theory of quasistationarity for absorbing Markov chains. We prove that the conditioned state probabilities of the original chain are equal to the state probabilities of its dual conditioned on non-absorption, thus allowing us to establish the simultaneous existence and then equivalence, of their limiting conditional distributions. Although a limiting conditional distribution for the dual chain is always a quasistationary distribution in the usual sense, a similar statement is not possible for the original chain.

Effect of density on spatial distribution, pit formation and pit diameter of Myrmeleon acer Walker, (Neuroptera : Myrmeleontidae): patterns and processes

The effect of increasing population density on the formation of pits, their size and spatial distribution, and on levels of mortality was examined in the antlion Myrmeleon acer Walker. Antlions were kept at densities ranging from 0.4 to 12.8 individuals per 100 cm(2). The distribution of pits was regular or uniform across all densities, but antlions constructed proportionally fewer and smaller pits as density increased. Mortality through cannibalism was very low and only occurred at densities greater than five individuals per 100 cm(2). Antlions in artificially crowded situations frequently relocated their pits and when more space became available, individuals became more dispersed with time. Redistribution of this species results from active avoidance of other antlions and sand throwing associated with pit construction and maintenance, rather than any attempt to optimise prey capture per se.

Further results on the relationship between mu-invariant measures and quasi-stationary distributions for absorbing continuous-time Markov chains

This note considers continuous-time Markov chains whose state space consists of an irreducible class, C, and an absorbing state which is accessible from C. The purpose is to provide results on mu-invariant and mu-subinvariant measures where absorption occurs with probability less than one. In particular, the well-known premise that the mu-invariant measure, m, for the transition rates be finite is replaced by the more natural premise that m be finite with respect to the absorption probabilities. The relationship between mu-invariant measures and quasi-stationary distributions is discussed. (C) 2000 Elsevier Science Ltd. All rights reserved.

An agent-based approach to modelling driver route choice behaviour under the influence of real-time information

This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters' responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers' behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief-desire-intention agent architecture. (C) 2002 Elsevier Science Ltd. All rights reserved.

Developing qualitative career assessment processes

Assessment has been integral to career counseling since the early 1900s. During that time, the greatest amount of attention was focused on quantitative assessment. Thus, there is still very little to guide the development and conduct of qualitative assessment in career counseling. The authors present an overview of qualitative career assessment and its theoretical underpinnings and propose suggestions that could guide the development of qualitative career assessment instruments.

Asymptotic behaviour of two-dimensional time-delayed Navier-Stokes equations

We consider the two-dimensional Navier-Stokes equations with a time-delayed convective term and a forcing term which contains some hereditary features. Some results on existence and uniqueness of solutions are established. We discuss the asymptotic behaviour of solutions and we also show the exponential stability of stationary solutions.

The selection of intended actions and the observation of others' actions: A time-resolved fMRI study

Whenever we plan, imagine, or observe an action, the motor systems that would be involved in preparing and executing that action are similarly engaged. The way in which such common motor activation is formed, however, is likely to differ depending on whether it arises from our own intentional selection of action or from the observation of another's action. In this study, we use time-resolved event-related functional MRI to tease apart neural processes specifically related to the processing of observed actions, the selection of our own intended actions, the preparation for movement, and motor response execution. Participants observed a finger gesture movement or a cue indicating they should select their own finger gesture to perform, followed by a 5-s delay period; participants then performed the observed or self-selected action. During the preparation and readiness for action, prior to initiation, we found activation in a common network of higher motor areas, including dorsal and ventral premotor areas and the pre-supplementary motor area (pre-SMA); the more caudal SMA showed greater activation during movement execution. Importantly, the route to this common motor activation differed depending on whether participants freely selected the actions to perform or whether they observed the actions performed by another person. Observation of action specifically involved activation of inferior and superior parietal regions, reflecting involvement of the dorsal visual pathway in visuomotor processing required for planning the action. In contrast, the selection of action specifically involved the dorsal lateral prefrontal and anterior cingulate cortex, reflecting the role of these prefrontal areas in attentional selection and guiding the selection of responses. (c) 2005 Elsevier Inc. All rights reserved.