Low-power 6-bit 1-GS/s two-channel pipeline ADC with open-loop amplification using amplifiers with local-feedback

IEEE International Symposium on Circuits and Systems, pp. 2258 – 2261, Seattle, EUA

Self-scheduling and bidding strategies of thermal units with stochastic emission constraints

This paper is on the self-scheduling problem for a thermal power producer taking part in a pool-based electricity market as a price-taker, having bilateral contracts and emission-constrained. An approach based on stochastic mixed-integer linear programming approach is proposed for solving the self-scheduling problem. Uncertainty regarding electricity price is considered through a set of scenarios computed by simulation and scenario-reduction. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. A requirement on emission allowances to mitigate carbon footprint is modelled by a stochastic constraint. Supply functions for different emission allowance levels are accessed in order to establish the optimal bidding strategy. A case study is presented to illustrate the usefulness and the proficiency of the proposed approach in supporting biding strategies. (C) 2014 Elsevier Ltd. All rights reserved.

Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.

A physical packing sequence algorithm for the container loading problem with static mechanical equilibrium conditions

The container loading problem (CLP) is a combinatorial optimization problem for the spatial arrangement of cargo inside containers so as to maximize the usage of space. The algorithms for this problem are of limited practical applicability if real-world constraints are not considered, one of the most important of which is deemed to be stability. This paper addresses static stability, as opposed to dynamic stability, looking at the stability of the cargo during container loading. This paper proposes two algorithms. The first is a static stability algorithm based on static mechanical equilibrium conditions that can be used as a stability evaluation function embedded in CLP algorithms (e.g. constructive heuristics, metaheuristics). The second proposed algorithm is a physical packing sequence algorithm that, given a container loading arrangement, generates the actual sequence by which each box is placed inside the container, considering static stability and loading operation efficiency constraints.

A survey of wireless technologies coexistence in WBAN: analysis and open research issues

Wireless Body Area Network (WBAN) is the most convenient, cost-effective, accurate, and non-invasive technology for e-health monitoring. The performance of WBAN may be disturbed when coexisting with other wireless networks. Accordingly, this paper provides a comprehensive study and in-depth analysis of coexistence issues and interference mitigation solutions in WBAN technologies. A thorough survey of state-of-the art research in WBAN coexistence issues is conducted. The survey classified, discussed, and compared the studies according to the parameters used to analyze the coexistence problem. Solutions suggested by the studies are then classified according to the followed techniques and concomitant shortcomings are identified. Moreover, the coexistence problem in WBAN technologies is mathematically analyzed and formulas are derived for the probability of successful channel access for different wireless technologies with the coexistence of an interfering network. Finally, extensive simulations are conducted using OPNET with several real-life scenarios to evaluate the impact of coexistence interference on different WBAN technologies. In particular, three main WBAN wireless technologies are considered: IEEE 802.15.6, IEEE 802.15.4, and low-power WiFi. The mathematical analysis and the simulation results are discussed and the impact of interfering network on the different wireless technologies is compared and analyzed. The results show that an interfering network (e.g., standard WiFi) has an impact on the performance of WBAN and may disrupt its operation. In addition, using low-power WiFi for WBANs is investigated and proved to be a feasible option compared to other wireless technologies.

Simulation of the velocity field in compound channel flow using different closure models

1st European IAHR Congress,6-4 May, Edinburg, Scotland

Ultrasound velocity profile (UVP) measurements in shallow open-channel flows

1st European IAHR Congress, 6-4 May, Edinburgh, Scotland

Flow resistance in open-channel flows with mobile hydraulically rough beds

River Flow 2008, Vol.1

Propagation of waves generated by a pressure disturbance moving in a channel

This paper studies the effect of ship speed and water depth on the propagation of ship generated waves. The ship is represented by a moving pressure distribution function at the free surface that is able to reproduce most of the phenomena involved in wave propagation. Results are obtained for a ship sailing along a coastal stretch made of a sloping bottom and a constant depth region. The results show that in the sloping bottom the crests of waves are bent along the slope and in the constant depth the standard Kelvin wave patterns can be found for the subcritical regime. In the critical regime the wave system is characterized by significant diverging waves and for a supercritical regime, the transverse waves disappear. © 2015 Taylor & Francis Group, London.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Hyperspectral imagery framework for unmixing and dimensionality estimation

In hyperspectral imagery a pixel typically consists mixture of spectral signatures of reference substances, also called endmembers. Linear spectral mixture analysis, or linear unmixing, aims at estimating the number of endmembers, their spectral signatures, and their abundance fractions. This paper proposes a framework for hyperpsectral unmixing. A blind method (SISAL) is used for the estimation of the unknown endmember signature and their abundance fractions. This method solve a non-convex problem by a sequence of augmented Lagrangian optimizations, where the positivity constraints, forcing the spectral vectors to belong to the convex hull of the endmember signatures, are replaced by soft constraints. The proposed framework simultaneously estimates the number of endmembers present in the hyperspectral image by an algorithm based on the minimum description length (MDL) principle. Experimental results on both synthetic and real hyperspectral data demonstrate the effectiveness of the proposed algorithm.

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

The role of Public Health Laboratory in the problem os salmonellosis in São Paulo, Brazil

From 1950 to 1990 a total of 45,862 strains (31,517 isolates from human sources, and 14,345 of non-human origin) were identified at Instituto Adolfo Lutz. No prevalence of any serovars was seen during the period 1950-66 among human sources isolates. Important changing pattern was seen in 1968, when S. Typhimurim surprisingly increased becoming the prevalent serovar in the following decades. During the period of 1970-76, S. Typhimurium represented 77.7% of all serovars of human origin. Significant rise in S. Agona isolation as well as in the number of different serovars among human sources strains were seen in the late 70' and the 80's. More than one hundred different serovars were identified among non-human origin strains. Among serovars isolated from human sources, 74.9%, 15.5%, and 3.7% were recovered from stool, blood, and cerebrospinal fluid cultures, respectively. The outbreak of meningitis by S. Grumpensis in the 60's, emphasizes the concept that any Salmonella serovars can be a cause of epidemics, mainly of the nosocomial origin. This evaluation covering a long period shows the important role of the Public Health Laboratory in the surveillance of salmonellosis, one of the most frequent zoonosis in the world.

Anemia de células falciformes na idade pediátrica : contribuição para o estudo das suas principais complicações e indicadores de prognóstico

RESMO: Introdução: A anemia de células falciformes doença hereditária, com repercussão multi-orgânica, tem grande variabilidade na sua expressão clínica. Daí o interesse do estudo de indicadores de prognóstico. A investigação realizada foi precedida de um resumo histórico incidindo sobre a compreensão de aspectos fundamentais da doença ao longo dos tempos. Na primeira parte do estudo e após revisão bibliográfica, foram referidos dados da fisiopatologia como base para os estudos que integram a presente dissertação. Abordou-se o estado da arte relativamente às complicações, aos indicadores de prognóstico e à terapêutica utilizada. Objectivos: Constituíram objectivos deste estudo realizado numa amostra populacional representativa: identificar as lesões a nível dos sistemas cardio-respiratório e nervoso central, avaliando-se as respectivas repercussões; avaliar a presença de indicadores de prognóstico entre as variáveis seleccionadas; estudar a eficácia e toxicidade da HU nos doentes com as formas graves da ACF. Para a prossecução destes objectivos foram delineados para além do estudo global três estudos específicos: Estudo 1- repercussão no sistema cardio-respiratório; Estudo 2- repercussão no sistema nervoso central; Estudo 3- terapêutica com hidroxiureia. Doentes e métodos: Procedeu-se a um estudo prospectivo e multi-institucional durante um período de três anos tendo-se seleccionado para a amostra, e de acordo com critérios pré-definidos, 30 doentes com ACF na fase estável da doença, com idades compreendidas entre os sete e os 18 anos, todos de origem africana à excepção de um caucasiano. O diagnóstico baseou-se em técnicas de electroforese e estudo molecular que definiu o genotipo da doença e a presença da delecção da -talassémia assim como os haplotipos da amostra populacional. Foram utilizadas diferentes metodologias para avaliar a existência de lesão pulmonar e cerebral. Através do estudo estatístico foram seleccionadas diversas variáveis como hipotéticos indicadores de prognóstico. Estudo 1. Para determinar a existência de lesão a nível pulmonar usaram-se duas metodologias diferentes, a avaliação da função pulmonar com estudo da saturação da Hb em O2 no sangue arterial e a tomografia computadorizada de alta resolução. Estudou-se também a possível disfunção cardíaca como repercussão da lesão pulmonar, através do ecocardiograma, e os indicadores de prognóstico com significado estatístico para a lesão encontrada. Estudo 2. O desenho deste estudo foi sobreponível ao anterior, mas com metodologia adequada para o SNC. Procedeu-se ao estudo das lesões cerebrais por meio de exames imagiológicos, (RMN-CE e DTC) e de testes psicológicos. Correlacionaram-se as três metodologias utilizadas e a importância de cada uma para a decisão de atitudes terapêuticas preventivas. Estudo 3. Consistiu num estudo aberto prospectivo não controlado com nove crianças e adolescentes com formas graves de ACF, com o objectivo de avaliar a eficácia da terapêutica com hidroxiureia, durante um período de 24 meses. Todos os doentes completaram no mínimo 15 meses de terapêutica, com uma dose final média de 194 mg/K/dia. Resultados globais: Durante o período anterior à investigação caracterizou-se a amostra populacional estudada quanto ao fenotipo genético, clínico e hematológico de acordo com os critérios utilizados por outros investigadores. Verificou-se: predomínio do haplotipo Bantu na forma homozigótica em 53% dos doentes; número total de EVO ≥3/ano em 87,5% dos doentes; crises de sequestração em 18,75%; dactilites no primeiro ano de vida em 31,2%; quadro de sépsis grave apenas num doente; crises de hiper-hemólise em 50%; e STA em 59,38% dos doentes. Quanto ao fenotipo hematológico evidenciaram-se como factores de risco reticulocitose (13,1x103/l) e hiperbilirrubinémia (2,5 mg/dl) e como factores de bom prognóstico a presença de delecção de um gene da -talassémia em 46,9% dos doentes e valor médio de Hb 8,1 g/dl. Resultados dos estudos parcelares: Estudo 1. Deste estudo infere-se que a DPR ligeira foi diagnosticada em 70% dos doentes, uma vez que as alterações da difusão não foram estatisticamente significativas, o estudo dos gases no sangue não evidenciaram resultados anormais e a TCAR evidenciou alterações em 43,3% dos doentes. Apenas num doente se verificou doença pulmonar obstrutiva relacionada com maior número da STA.O estudo da disfunção cardíaca encontrada em 86,7% dos doentes não reflecte a repercussão da DPR a nível cardíaco, podendo estar associada às alterações fisiopatológicas da própria anemia crónica. Encontraram-se indicadores de prognóstico hematológicos e clínicos. Entre os primeiros, valores de Hb ≥8,5 g/dl e de HbF ≥13% foram considerados indicadores de bom prognóstico para a lesão pulmonar. Em relação aos parâmetros clínicos, as STA não foram consideradas indicadoras de prognóstico para a DPR ao contrário do que se verificou com o número de EVO. Pela análise dos parâmetros genéticos e socio-económicos provou-se a ausência de relação estatisticamente significativa com lesão pulmonar. Estudo 2. Pela RMN-CE foram diagnosticados ES em 33,3% com uma localização preferencial na substância branca profunda em 26,6% dos doentes. Relativamente aos parâmetros hematológicos seleccionados, o valor médio da HbF 8,6% constituíu um indicador de bom prognóstico para o aparecimento de ES, enquanto o valor médio de leucócitos 12.39x103/μl foi considerado um indicador de mau prognóstico. No estudo do DTC apenas um doente apresentou aumento da velocidade do fluxo cerebral na ACM igual a 196 cm/segundos, associado a vasculopatia grave. Os testes psicológicos alterados em 80% dos doentes mostraram ser o método mais sensível para detectar alterações do neurodesenvolvimento, mas sem correlação com os ES em 10% dos doentes. Realça-se a baixa percentagem de DTC patológicos encontrados neste estudo em relação ao número elevado de ES e de testes psicológicos alterados, não se verificando concordância entre os três exames. Dos indicadores de prognóstico estudados a -talassémia foi considerada um factor de protecção para o coeficiente de inteligência da escala de Wechsler. Em relação a parâmetros clínicos estudados os doentes com maior número de EVO, tem em média valores inferiores nos testes psicológicos. Estudo 3. Neste estudo verificou-se que o valor médio da HbF aumentou significativamente de 7,0±4% para 13,7±5,3% (p=0,028) ao fim de 15 meses de terapêutica com hidroxiureia. Clinicamente todos os doentes responderam significativamente com uma redução de 80% no número de EVO, 69% no número de internamentos, 76% no número de dias de hospitalização e 67% no número de transfusões. Deste modo comprovou-se não só a eficácia desta terapêutica neste grupo pediátrico como também a falta de efeitos secundários significativos. Considera-se a necessidade de estudos mais prolongados e em grande séries, para com segurança se usar a HU antes que a lesão orgânica se estabeleça, portanto logo nos primeiros anos de vida. Conclusão: Na amostra populacional estudada foram evidenciadas lesões pulmonares e cerebrais na grande maioria dos doentes que condicionaram a sua qualidade de vida. Foram identificados indicadores de prognóstico que poderão eventualmente ditar medidas terapêuticas precoces com o objectivo de diminuir a morbilidade e a mortalidade neste grupo etário. Demonstrou-se que a terapêutica com a HU foi eficaz e bem tolerada----------ABSTRACT: Background: Sickle cell anemia (SCA), a hereditary disease characterized by pain and lifetime multi-organic lesion, is a challenge for all that work with carriers of this disease. The clinical expression variability of SCA is a constant reality and a problem to be solved in the current world of investigation, for which the knowledge of prognostic indicators responsible for the different aspects of clinical evolution diversity wiil be an added value. The study is preceded by a historical summary of the most important factors in the evolution of SCA, which are in themselves, an incentive for future research. In the first part of the study, after an extensive bibliographical revision, physiopathology data is referred to in general and specifically regarding the target organs, that constituted the base for the studies presented in the dissertation. The state of the art for the complications to be studied, the choice of prognostic indicators and the therapeutics application, were approached for the renewed interest in the theme. Aims: In regard to the investigation, the objective was to study the lesions in the most affected organs of a chosen pediatric group, to investigate prognostic indicators for lung and cerebral lesions and to evaluate the protective effect of hydroxyurea in children with severe outcomes. Patients and methods: A prospective and multi-institutional study was carried out during a three-year period, February 1998 to March 2001, with children and adolescents followed up at a Immunohematology Outpatient Clinic of Dona Estefânia's Hospital, Lisbon. Based in predefined criteria, 30 children with SCA were selected in a stable phase of the disease, aged from seven to 18 years old, all of whom were of African origin with exception of one who was Caucasian. The diagnosis was based on electrophoresis techniques and molecular study that allowed to define the genotype, the presence of deletional alpha-thalassemia as well as haplotypes in the population. Different methodologies were used to evaluate the existence of lung and cerebral lesion. Statistical study of the different variables selected the prognostic indicators. In Study 1, to determine the existence of lung lesion two different methodologies were used: pulmonar function study with arterial blood gases determination; and high resolution computerized tomography. Heart dysfunction as a repercussion of lung lesion was also studied through echocardiography, and prognostic indicators were statistically significant for lesions found. The design of Study 2 was similar to Study 1, but with the appropriate methodology for CNS. After neurological examination, which was normal in all patients (control group), cerebral lesions were studied with imagiologic exams (MRN-CE and TCD) and psychological tests. These three methodologies were correlated and the importance of each one in the decision of the therapeutic profilactic attitudes. Study 3 consisted of a controlled prospective open study in children with severe forms of SCA, with the aim of the evaluating therapeutic effectiveness of hydroxyurea, during a period of 24 months. Results: In the global overall study preceding the Studies 1,2 and 3, there were a prevalence of haplotype Bantu (53%) and other risk factors, namely the number of VOC (87,5%), sequestration crisis (18,75%), dactilytis in first year of life(31,2%), hyperhemolysis crisis (50%) and ATC in more than half of the patients (59,38%). This group of bad prognostic indicators, associated with the population of the lower class according to the Graffar scale, demonstrates the importance of primary health care services, information provided to the children and their relatives, as well as the interest in prophylactic therapeutics, specific screening and prenatal diagnosis. Study 1. It was evident from this study that slight RPD was diagnosed in 70% of the patients, because alterations of the diffusion had no statistical significance and arterial blood gases determinations were normal. Only one patient had restrictive lung disease related with numerous ACS. However ACS was not considered a prognostic indicator for RPD, contrary to the number of EVO. HRTC revealed discreet fibrotic lines that could be related with slight RPD, but the lack of correlation of these two exams (33%) supports the value of lung function tests for precocious diagnosis of RPD. Heart dysfunction was found in 86,7% of patients, does not reflect the repercussion of RPD, but with the physiopathology of chronic anemia. Hematologic and clinical prognostic indicators were found. Good prognostic indicators for the non-evolution of RPD with average Hb values of ≥ 8,5 g/dl and average HbF values of ≥13%, respectively. The genetic and social-economic factors had no statistical significance; nevertheless, they were more prevalent among Bantu haplotype (53,3%) in patients with RPD. Study 2. RMN-CE detected SI in 33,3% of the patients, with preferential location in deep white substance in 26,6% and in front lobe in 20%. This distribution can be related to structural aspects of the brain and with the high sensibility of this organ to hypoxia. From the hematological parameters selected, average HbF value 8,6% and average leucocyte count 12.39x103/μl were prognostic indicators with different meaning to SI. The increase in the total bilirubin related to hyperhemolysis clinically explains the genesis of SI In the TCD study, only one patient had increased cerebral flow speed >196 cm/sec in CMA, which corresponded to serious vasculopathy in AngioMR. This patient never present previously neurological symptoms and had several hyperhemolysis crisis and VOC as risk factors. Low percentage of pathological TCD in this study, in relation to the high number of SI and altered tests, although without correlation among the three exams, is probably attributed to factors related to the methodology, aspects of cerebral physiopathology or perhaps a sign of good prognostic if the duration of study had not been so short. TCD should be used as a screening method in the age groups with higher risk of AVC and should never be considered separately in prophylactic therapeutics indication. Psychological tests were the most sensitive method to detect neurodevelopment impairment; in 80% of patients the neuropsychologics tests were altered, but without correlation with SI (10%). Since SI can become evident during the first two years of life and develop with time, the first psychological tests should be carried out between 3 and 5 years of age to timely be referred to special education and stimulation programs. Prognostic indicators to psychological tests were also found: alpha-thalassemia was found to be a protection factor of the IQ, just as other hematologic factors (hematocrit, MGCV and erythrocytes count). In relation to clinical parameters, although without statistical significance, patients with larger number of VOC had average lower scores versus the average in tests, except in TP. Results from different studies were conclusive as to the type of lesion found and the importance of prognostic indicators. Study 3. All the patients completed a minimum of 15 months therapeutic treatment with the final average daily dose of 19±4 mg/kg/day. The average value of the fetal hemoglobin increased significantly from 7,0±3,9% to 13,7±5,3% (p=0.028). The HbF average values increased from 6% to 15% after 15 months of therapeutic treatment. Clinically there was a reduction of 80% in the number of VOE , 69% in the number of hospitalization, 76% in the number of days of hospitalization and 67% in the number of transfusions. Once again the effectiveness of this treatment in this pediatric group, as well as the lack of any significant secondary effects, was evident. The study confirms the need for further detailed research in order to safely effect the appropriate treatment prior to the development of organic lesions, which ideally should be in the first year of life. Conclusions: These results allow us to clarify the importance of either pulmonary lesions or either nervous central system impairment among patients, children and adolescents, with sickle cell anemia. These lesions were demonstrated in most of the patients studied compromising their quality of life and the mortality. The treatment with HU is proved to be effective and having low toxicity.

Using interval graphs in an order processing optimization problem

In this paper we address an order processing optimization problem known as minimization of open stacks (MOSP). We present an integer pro gramming model, based on the existence of a perfect elimination scheme in interval graphs, which finds an optimal sequence for the costumers orders.