A Separation Principle for the Continuous-Time LQ-Problem With Markovian Jump Parameters

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.

On the Filtering Problem for Continuous-Time Markov Jump Linear Systems with no Observation of the Markov Chain

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.

New simple and efficient heuristics for the uncapacitated single allocation hub location problem

Hub-and-spoke networks are widely studied in the area of location theory. They arise in several contexts, including passenger airlines, postal and parcel delivery, and computer and telecommunication networks. Hub location problems usually involve three simultaneous decisions to be made: the optimal number of hub nodes, their locations and the allocation of the non-hub nodes to the hubs. In the uncapacitated single allocation hub location problem (USAHLP) hub nodes have no capacity constraints and non-hub nodes must be assigned to only one hub. In this paper, we propose three variants of a simple and efficient multi-start tabu search heuristic as well as a two-stage integrated tabu search heuristic to solve this problem. With multi-start heuristics, several different initial solutions are constructed and then improved by tabu search, while in the two-stage integrated heuristic tabu search is applied to improve both the locational and allocational part of the problem. Computational experiments using typical benchmark problems (Civil Aeronautics Board (CAB) and Australian Post (AP) data sets) as well as new and modified instances show that our approaches consistently return the optimal or best-known results in very short CPU times, thus allowing the possibility of efficiently solving larger instances of the USAHLP than those found in the literature. We also report the integer optimal solutions for all 80 CAB data set instances and the 12 AP instances up to 100 nodes, as well as for the corresponding new generated AP instances with reduced fixed costs. Published by Elsevier Ltd.

Heroin-assisted treatment as a response to the public health problem of opiate dependence

Injection drug use (involving the injection of illicit opiates) poses serious public health problems in many countries. Research has indicated that injection drug users are at higher risk for morbidity in the form of HIV/AIDS and Hepatitis B and C, and drug-related mortality, as well as increased criminal activity. Methadone maintenance treatment is the most prominent form of pharmacotherapy treatment for illicit opiate dependence in several countries, and its application varies internationally with respect to treatment regulations and delivery modes. In order to effectively treat those patients who have previously been resistant to methadone maintenance treatment, several countries have been studying and/or considering heroin-assisted treatment as a complementary form of opiate pharmacotherapy treatment. This paper provides an overview of the prevalence of injection drug use and the opiate dependence problem internationally, the current opiate dependence treatment landscape in several countries, and the status of ongoing or planned heroin-assisted treatment trials in Australia, Canada and certain European countries.

QUADRANT-SEARCHING: A NEW TECHNIQUE TO REDUCE THE SEARCH SPACE OF THE INVERSE PROBLEM OF EIT USING BEM TO THE DIRECT PROBLEM

The image reconstruction using the EIT (Electrical Impedance Tomography) technique is a nonlinear and ill-posed inverse problem which demands a powerful direct or iterative method. A typical approach for solving the problem is to minimize an error functional using an iterative method. In this case, an initial solution close enough to the global minimum is mandatory to ensure the convergence to the correct minimum in an appropriate time interval. The aim of this paper is to present a new, simple and low cost technique (quadrant-searching) to reduce the search space and consequently to obtain an initial solution of the inverse problem of EIT. This technique calculates the error functional for four different contrast distributions placing a large prospective inclusion in the four quadrants of the domain. Comparing the four values of the error functional it is possible to get conclusions about the internal electric contrast. For this purpose, initially we performed tests to assess the accuracy of the BEM (Boundary Element Method) when applied to the direct problem of the EIT and to verify the behavior of error functional surface in the search space. Finally, numerical tests have been performed to verify the new technique.

Mild myocardial infarction - A classification problem in epidemiologic studies

In studies assessing the trends in coronary events, such as the World Health Organization (WHO) MONICA Project (multinational MONItoring of trends and determinants of CArdiovascular disease), the main emphasis has been on coronary deaths and non-fatal definite myocardial infarctions (MI). It is, however, possible that the proportion of milder MIs may be increasing because of improvements in treatment and reductions in levels of risk factors. We used the MI register data of the WHO MONICA Project to investigate several definitions for mild non-fatal MIs that would be applicable in various settings and could be used to assess trends in milder coronary events. Of 38 populations participating in the WHO MONICA MI register study, more than half registered a sufficiently wide spectrum of events that it was possible to identify subsets of milder cases. The event rates and case fatality rates of MI are clearly dependent on the spectrum of non-fatal MIs, which are included. On clinical grounds we propose that the original MONICA category ''non-fatal possible MI'' could bt:divided into two groups: ''non fatal probable MI'' and ''prolonged chest pain.'' Non-fatal probable MIs are cases, which in addition to ''typical symptoms'' have electrocardiogram (EGG) or enzyme changes suggesting cardiac ischemia, but not severe enough to fulfil the criteria for non-fatal definite MI In more than half of the MONICA Collaborating Centers, the registration of MI covers these milder events reasonably well. Proportions of non-fatal probable MIs vary less between populations than do proportions of non fatal possible MIs. Also rates of non-fatal probable MI are somewhat more highly correlated with rates of fatal events and non-fatal definite MI. These findings support the validity of the category of non-fatal probable MI. In each center the increase in event rates and the decrease in case-fatality due to the inclusion of non-fatal probable MI was lar er for women than men. For the WHO MONICA Project and other epidemiological studies the proposed category of non-fatal probable MIs can be used for assessing trends in rates of milder MI. Copyright (C) 1997 Elsevier Science Inc.

The intersection problem for K_4-e designs

A G-design of order n is a pair (P,B) where P is the vertex set of the complete graph K-n and B is an edge-disjoint decomposition of K-n into copies of the simple graph G. Following design terminology, we call these copies ''blocks''. Here K-4 - e denotes the complete graph K-4 with one edge removed. It is well-known that a K-4 - e design of order n exists if and only if n = 0 or 1 (mod 5), n greater than or equal to 6. The intersection problem here asks for which k is it possible to find two K-4 - e designs (P,B-1) and (P,B-2) of order n, with \B-1 boolean AND B-2\ = k, that is, with precisely k common blocks. Here we completely solve this intersection problem for K-4 - e designs.

The application of adaptive partitioned random search in feature selection problem

Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.

Selecting methods to solve multi-well master equations

There are several competing methods commonly used to solve energy grained master equations describing gas-phase reactive systems. When it comes to selecting an appropriate method for any particular problem, there is little guidance in the literature. In this paper we directly compare several variants of spectral and numerical integration methods from the point of view of computer time required to calculate the solution and the range of temperature and pressure conditions under which the methods are successful. The test case used in the comparison is an important reaction in combustion chemistry and incorporates reversible and irreversible bimolecular reaction steps as well as isomerizations between multiple unimolecular species. While the numerical integration of the ODE with a stiff ODE integrator is not the fastest method overall, it is the fastest method applicable to all conditions.

A global health problem caused by arsenic from natural sources

Arsenic is a carcinogen to both humans and animals. Arsenicals have been associated with cancers of the skin, lung, and bladder. Clinical manifestations of chronic arsenic poisoning include non-cancer end point of hyper- and hypo-pigmentation, keratosis, hypertension, cardiovascular diseases and diabetes. Epidemiological evidence indicates that arsenic concentration exceeding 50 mug l(-1) in the drinking water is not public health protective. The current WHO recommended guideline value for arsenic in drinking water is 10 mug l(-1), whereas many developing countries are still having a value of 50 mug 1(-1). It has been estimated that tens of millions of people are. at risk exposing to excessive levels of arsenic from both contaminated water and arsenic-bearing coal from natural sources. The global health implication and possible intervention strategies were also discussed in this review article. (C) 2003 Elsevier Ltd. All rights reserved.

Annotation taken, in the perspective of criminal and constitutional law, as well as in criminology, to the decision of the portuguese constitutional court, of January 13, 2011 – with respect to the problems of “consent” and “medical act”

1 – Summary of the decision taken by the Portuguese Constitutional Court, of January 13, 2011; 2 – Complete text of the decision of the Portuguese Constitutional Court, of January 13, 2011, Judge Maria João ANTUNES (Reporter), Judge Carlos Pamplona de OLIVEIRA, Judge José Borges SOEIRO, Judge Gil GALVÃO, Judge Rui Manuel Moura RAMOS (President) –in terms of the tribunalconstitucional.pt, August 1, 2011; 3 – Brief annotation to the problem of the “medical act”; 3.1 – Plus some conclusions on the brief annotation to the problem of the “medical act”; 3.2 – Brief annotation to the problem of “consent”– continuation of the previous comments; 4 – Conclusions. It must never be forgotten that “consent” does not stand as the only cause of exclusion of unlawfulness.

The problem of estimating the volatility of zero coupon bond interest rate

Financial literature and financial industry use often zero coupon yield curves as input for testing hypotheses, pricing assets or managing risk. They assume this provided data as accurate. We analyse implications of the methodology and of the sample selection criteria used to estimate the zero coupon bond yield term structure on the resulting volatility of spot rates with different maturities. We obtain the volatility term structure using historical volatilities and Egarch volatilities. As input for these volatilities we consider our own spot rates estimation from GovPX bond data and three popular interest rates data sets: from the Federal Reserve Board, from the US Department of the Treasury (H15), and from Bloomberg. We find strong evidence that the resulting zero coupon bond yield volatility estimates as well as the correlation coefficients among spot and forward rates depend significantly on the data set. We observe relevant differences in economic terms when volatilities are used to price derivatives.

Fungal contamination of poultries litter: a public health problem

Exposure to certain fungi can cause human illness. Fungi cause adverse human health effects through three specific mechanisms: generation of a harmful immune response (e.g., allergy or hypersensitivity pneumonitis); direct infection by the fungal organism; by toxic-irritant effects from mold byproducts, such as mycotoxins. In Portugal there is an increasingly industry of large facilities that produce whole chickens for domestic consumption and only few investigations have reported on fungal contamination of the poultry litter. The material used for poultry litter is varied but normally can be constitute by: pine shavings; sawdust of eucalyptus; other types of wood; peanut; coffee; sugar cane; straw; hay; grass; paper processed. Litter is one of the most contributive factors to fungal contamination in poultries. Spreading litter is one of the tasks that normally involve higher exposure of the poultry workers to dust, fungi and their metabolites, such as VOC’s and mycotoxins. After being used and removed from poultries, litter is ploughed into agricultural soils, being this practice potentially dangerous for the soil environment, as well for both humans and animals. The goal of this study was to characterize litter’s fungal contamination and also to report the incidence of keratinophilic and toxigenic fungi.

Fungal contamination of poultry litter: a public health problem

Although numerous studies have been conducted on microbial contaminants associated with various stages related to poultry and meat products processing, only a few reported on fungal contamination of poultry litter. The goals of this study were to (1) characterize litter fungal contamination and (2) report the incidence of keratinophilic and toxigenic fungi presence. Seven fresh and 14 aged litter samples were collected from 7 poultry farms. In addition, 27 air samples of 25 litters were also collected through impaction method, and after laboratory processing and incubation of collected samples, quantitative colony-forming units (CFU/m3) and qualitative results were obtained. Twelve different fungal species were detected in fresh litter and Penicillium was the most frequent genus found (59.9%), followed by Alternaria (17.8%), Cladosporium (7.1%), and Aspergillus (5.7%). With respect to aged litter, 19 different fungal species were detected, with Penicillium sp. the most frequently isolated (42.3%), followed by Scopulariopsis sp. (38.3%), Trichosporon sp. (8.8%), and Aspergillus sp. (5.5%). A significant positive correlation was found between litter fungal contamination (CFU/g) and air fungal contamination (CFU/m3). Litter fungal quantification and species identification have important implications in the evaluation of potential adverse health risks to exposed workers and animals. Spreading of poultry litter in agricultural fields is a potential public health concern, since keratinophilic (Scopulariopsis and Fusarium genus) as well as toxigenic fungi (Aspergillus, Fusarium, and Penicillium genus) were isolated.

Ant colony search algorithm for the optimal power flow problem

To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization problems. This paper presents an implementation of Ant Colony optimization to solve the OPF in an economic dispatch context. The proposed methodology has been developed to be used for maintenance and repairing planning with 48 to 24 hours antecipation. The main advantage of this method is its low execution time that allows the use of OPF when a large set of scenarios has to be analyzed. The paper includes a case study using the IEEE 30 bus network. The results are compared with other well-known methodologies presented in the literature.