Micronutrients intake associated with DNA damage assessed by in a human biomonitoring study

Nutrition science has evolved into a multidisciplinary field that applies molecular biology and integrates individual health with the epidemiologic investigation of population health. Nutritional genomics studies the functional interaction of food and its components, macro and micronutrients, with the genome at the molecular, cellular, and systemic level. Diet can influence cancer development in several ways, namely direct action of carcinogens in food that can damage DNA, diet components (macro or micronutrients) that can block or induce enzymes involved in activation or deactivation of carcinogenic substances. Moreover, inadequate intake of some molecules involved in DNA synthesis, repair or methylation can influence mutation rate or changes in gene expression. Several studies support the idea that diet can influence the risk of cancer; however information concerning the precise dietary factor that determines human cancer is an ongoing debate. A lot of epidemiological studies, involving food frequency questionnaires, have been developed providing important information concerning diet and cancer, however, diet is a complex composite of various nutrients (macro and micronutrients) and non-nutritive food constituents that makes the search for specific factors almost limitless.

Remediação de solos contaminados por compostos farmacêuticos

O recente surgimento de nanopartículas de ferro valente-zero (nFZV), um material com elevada capacidade de remediação de solos por via de reacções de oxidação/redução pode ser uma opção viável para a remoção de fármacos do solo. A sua aplicação já é uma realidade em alguns tipos de solos contaminados por compostos específicos e, com este trabalho, procura-se estudar a sua capacidade de remediação de solos contaminados por compostos farmacêuticos, recorrendo-se a uma tecnologia “verde” de síntese destas nanopartículas. Esta tecnologia é bastante recente, ainda não aplicada no campo de trabalho, que se baseia no uso de folhas de certas árvores para produzir extratos naturais que reduzem o ferro (III) a ferro zero valente, formando nFZV. Desta forma procedeu-se, à escala laboratorial, ao estudo da eficiência das nFZV na degradação de um fármaco – paracetamol – e comparou-se com a eficiência demonstrada por oxidantes, muito utilizados hoje em dia em casos de remediação in situ como o permanganato de potássio, o peróxido de hidrogénio, o persulfato de sódio e o reagente de Fenton. O estudo foi efectuado em dois meios diferentes: solução aquosa e solo arenoso. De forma muito sucinta, o estudo baseou-se na introdução dos oxidantes/nFZV em soluções/solos contaminados com paracetamol e consequente monitorização do processo de remediação através de cromatografia líquida de alta eficiência. Nos ensaios com soluções aquosas contaminadas com paracetamol, o permanganato de potássio e o reagente de Fenton revelaram capacidade para degradar o paracetamol, atingindo mesmo um grau de degradação de 100%. O persulfato de sódio também demonstrou uma capacidade de degradação do paracetamol, chegando a atingir 99% de degradação, mas apenas recorrendo ao uso de um volume de oxidante elevado quando comparado com os outros dois oxidantes já referidos. Por outro lado, o peróxido de hidrogénio não demonstrou qualquer capacidade de degradação do paracetamol, pelo que o seu uso não passou desta fase. Verificou-se também que o uso de ferro granulado para o tratamento de água contaminada com paracetamol revelou resultados diferentes dos observados no uso de nFZV, obtendo-se eficiências de 87%. Existiram dificuldades analíticas na quantificação do paracetamol, especificamente relacionadas com o uso do extracto de folhas de amoreira, cuja composição continha substâncias que causaram dificuldades acentuadas na análise dos cromatogramas. Por fim, um pequeno teste de combinação do reagente de Fenton com os fenómenos de biodegradação resultantes dos microrganismos presentes em folhas do extracto de chá preto demonstrou que este pode ser uma área que pode e deve ser mais estudada. Desta forma, a utilização das nFZV para o tratamento de água contaminada com paracetamol não permitiu a retirada de conclusões seguras sobre a capacidade que as nFZV produzidas com extractos de folhas de amoreira e de chá preto têm de degradação do paracetamol. Nos testes de remediação de solos contaminados os resultados demonstraram que, mais uma vez, tanto o permanganato de potássio como o reagente de Fenton se revelam como os melhores oxidantes para a degradação do paracetamol, obtendo-se a degradação total do paracetamol. Por outro lado, voltou a ser necessário uma elevada quantidade de persulfato de sódio quando comparada com os dois anteriores, para que ocorra a degradação desta mesma quantidade de paracetamol, demonstrando mais uma vez que, apesar de não ideal, o persulfato demonstra capacidade de degradação do paracetamol.

Alternative chelating agents: Evaluation of the ready biodegradability and complexation properties

The ready biodegradability of four chelating agents, N,N -(S,S)-bis[1-carboxy-2-(imidazol-4-yl)ethyl]ethylenediamine (BCIEE), N - ethylenedi-L-cysteine (EC), N,N -bis (4-imidazolymethyl)ethylenediamine (EMI) and 2,6-pyridine dicarboxylic acid (PDA), was tested according to the OECD guideline for testing of chemicals. PDA proved to be a readily biodegradable substance. However, none of the other three compounds were degraded during the 28 days of the test. Chemical simulations were performed for the four compounds in order to understand their ability to complex with some metal ions (Ca, Cd, Co, Cu, Fe, Mg, Mn, Ni, Pb, Zn) and discuss possible applications of these chelating agents. Two different conditions were simulated: (i) in the presence of the chelating agent and one metal ion, and (ii) in the simultaneous presence of the chelating agent and all metal ions with an excess of Ca. For those compounds that were revealed not to be readily biodegradable (BCIEE, EC and EMI), applications were evaluated where this property was not fundamental or even not required. Chemical simulations pointed out that possible applications for these chelating agents are: food fortification, food process, fertilizers, biocides, soil remediation and treatment of metal poisoning. Additionally, chemical simulations also predicted that PDA is an efficient chelating agent for Ca incrustations removal, detergents and for pulp metal ions removal process.

Comportamentos de sexo seguro em individuos infectados por VIH

A investigação científica que se seguiu à descoberta da infecção pelo vírus da imunodeficiência humana (VIH) representou um marco histórico importante, permitindo a instituição de terapêutica e alterando a história natural da infecção, melhorando as expectativas dos indivíduos infectados.Se, por um lado, a terapêutica antirretroviral de alta eficácia (do inglês, Highly Active Antiretroviral Theraphy: HAART), nos países desenvolvidos, teve um enorme impacto na melhoria da qualidade de vida e esperança média de vida dos indivíduos infectados, permitindo-lhes encarar a infecção como uma doença crónica, por outro lado, introduziu-se uma nova dinâmica epidemiológica na transmissão de VIH e um novo desafio para a sua prevenção.Os comportamentos sexuais são o factor-alvo através do qual se pode, de uma forma mais eficaz, prevenir a possibilidade de infectar um qualquer indivíduo na comunidade. Parece, pois, importante haver necessidade de um olhar atento da Saúde Pública sobre a vida sexual dos indivíduos infectados, não só na tentativa de, promover a sua qualidade de vida, como também, de prevenir a disseminação da doença, e, ainda mais importante, prevenir a disseminação do vírus nas suas formas resistentes.O objectivo deste estudo foi analisar a consistência do uso de preservativo/práticas de sexo seguro, em indivíduos infectados por VIH, seguidos em Consulta de Imunodepressão, do Serviço de Doenças Infecciosas, do Hospital de Santa Maria. Pretende-se avaliar, no âmbito da “Educação para a Saúde”, a necessidade de aconselhamento aos indivíduos infectados, relativamente aos seus comportamentos sexuais.Para o efeito, realizou-se um estudo descritivo e transversal. A população envolvida compreendeu todos os indivíduos infectados seguidos na Consulta de Imunodepressão. A amostra foi seleccionada através de aleatorização simples e constituída por 98 elementos. A colheita de dados foi efectuada através do método de entrevista, a qual só teve início após a assinatura do consentimento informado. O estudo decorreu entre 14 de Março e 27 de Junho de 2008.Foram analisados os dados relativamente às variáveis: sócio-demográficas, estado serológico da infecção, história sexual, consumo de substâncias, comportamento sexual e percepção de risco da transmissão da infecção por VIH.Os comportamentos de sexo não seguro foram associados ao número de parceiros sexuais/ano (p=0,007), ter parceiro sexual habitual (p=0,010), ter múltiplos parceiros sexuais ocasionais (p=0,000) e à prática de sexo oral (sexo oral receptivo, p=0,001; sexo oral activo, p=0,006).Os resultados demonstraram a importância da prevenção secundária nos indivíduos infectados por VIH. A necessidade dos centros de atendimento estarem providos de mensagem de prevenção, ensinos e aconselhamento a todas as pessoas infectadas e, também, aos seus parceiros sexuais, aumentando-lhes a qualidade de vida e reduzindo o risco de transmissão da infecção por HIV. ABSTRACT: The scientific research that followed the finding of human immunodeficiency virus (HIV) infection represented an important historical mark, allowing therapeutic institution and changing the natural history of the infection, thus improving the expectations of infected individuals. If by one side the Highly Active Antiretroviral Therapy (HAART) had an enormous impact on the improvement of life quality and life expectancy of the infected individuals on the developed countries, allowing them to face the infection as a chronic disease, on the other side it was introduced a epidemiologic dynamic on the HIV transmission and a new challenge for its prevention. Sexual behaviour is the main factor through which is possible to prevent more efficiently the possibility of infection of a community’s individual. Thus it appears important the need of Public Health to have a careful look into the sexual life of infected individuals, not only to try to promote their life quality but as well to prevent the dissemination of the disease and more importantly prevent the dissemination of the virus in its resistant forms. The objective of this study was to analyse the consistency of the use of condoms/safe sex by individuals infected by HIV that are followed by the Infectious Disease Service of the Santa Maria Hospital through Immune-depression Appointments. The goal was to evaluate the need of advisement to the infected individuals relatively to their sexual behaviours. For that it was done a descriptive and transversal study. The involved population included all infected individuals followed in the Immune-depression Appointments. The sample was selected by simple randomisation and was composed by 98 elements. The data was obtained by interview method, which was initiated after signing the informed consent. The study was took place between 14 March and 27 June 2008. It was analysed the data relative to the variables: socio-demographics, serologic state of the infection, sexual history, substances consumption, sexual behaviour and risk perception on the transmission of HIV infection. The unsafe sexual behaviours were associated to the number of sexual partners/year (p=0,007), having steady partner (p= 0,010), having occasional sexual partners (p=0,000) and oral sex practice (receptive oral sex, p=0,001; active oral sex, p= 0,006).The results demonstrated the importance of the secondary prevention on individuals infected by HIV. It also demonstrated the need of providing the attendance centres with a prevention message, teachings and advises to all infected persons as well as to their sexual partners, increasing their life quality and reducing the transmission risk of HIV infection.

Evaluation in white mice of the infectivity of egs of Lagochilascaris minor (Nematoda: ascarididae), incubated by decortication with sodium hypochlorite (NaOCl)

White mice were used to study the infectivity of the eggs of Lagochilascaris minor Leiper, 1909 after incubation in liquid media, with or without preservative substances. Potassium bichromate (K2Cr2O7) at 1% restrict hatching, while 1% formalin gave a greater larval yield. Incubation of eggs in distilled water, in Roux or Falcon flasks gave a good yield, whether the eggs were obtained from human feces or from experimentally infected cats. Treatment of eggs with Sodium hypochlorite (NaOCl) at 5.25% for 2 min prior to inoculation, produced a notable increment of the larval yield in the infections.

Behaviour and fate of metals in urban wastewater treatment plants: a review

The concerns on metals in urban wastewater treatment plants (WWTPs) are mainly related to its contents in discharges to environment, namely in the final effluent and in the sludge produced. In the near future, more restrictive limits will be imposed to final effluents, due to the recent guidelines of the European Water Framework Directive (EUWFD). Concerning the sludge, at least seven metals (Cd, Cr, Cu, Hg, Ni, Pb and Zn) have been regulated in different countries, four of which were classified by EUWFD as priority substances and two of which were also classified as hazardous substances. Although WWTPs are not designed to remove metals, the study of metals behaviour in these systems is a crucial issue to develop predictive models that can help more effectively the regulation of pre-treatment requirements and contribute to optimize the systems to get more acceptable metal concentrations in its discharges. Relevant data have been published in the literature in recent decades concerning the occurrence/fate/behaviour of metals in WWTPs. However, the information is dispersed and not standardized in terms of parameters for comparing results. This work provides a critical review on this issue through a careful systematization, in tables and graphs, of the results reported in the literature, which allows its comparison and so its analysis, in order to conclude about the state of the art in this field. A summary of the main consensus, divergences and constraints found, as well as some recommendations, is presented as conclusions, aiming to contribute to a more concerted action of future research. © 2015, Islamic Azad University (IAU).

Schistosoma mansoni: the effect of dexamethasone on the cercaria-schistosomulum transformation, in vivo

Treatment with dexamethasone (DMS) in the early phases of the experimental Schistosoma mansoni infection causes an indirect effect on the cercaria-schistosomulum transformation process. This is observed when naive albino mice are treated with that drug (50 mg/Kg, subcutaneously) and infected intraperitonealy 01 hour later with about 500 S. mansoni cercariae (LE strain). An inhibition in the host cell adhesion to the larvae, with a simultaneous delay in the cercaria-schistosomulum transformation, is observed. This effect is probably due to a blockade of the neutrophil migration to the peritoneal cavity of mice, by an impairment of the release of chemotactic substances. Such delay probably favors the killing of S. mansoni larvae, still in the transformation process, by the vertebrate host defenses, as the complement system.

Fast unsupervised technique for extraction of endmembers spectra from hyperspectral data

One of the most challenging task underlying many hyperspectral imagery applications is the linear unmixing. The key to linear unmixing is to find the set of reference substances, also called endmembers, that are representative of a given scene. This paper presents the vertex component analysis (VCA) a new method to unmix linear mixtures of hyperspectral sources. The algorithm is unsupervised and exploits a simple geometric fact: endmembers are vertices of a simplex. The algorithm complexity, measured in floating points operations, is O (n), where n is the sample size. The effectiveness of the proposed scheme is illustrated using simulated data.

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.

Desenvolvimento de código pictográfico para identificação de medicamentos

Trabalho de Projeto

Consumo de Fitoterápicos no Distrito de Viana do Castelo

A fitoterapia é umas das Medicinas Alternativas e/ou Complementares mais utilizadas pela população no quotidiano. Esta terapêutica é constituída por misturas de compostos químicos, que são responsáveis pelas suas ações no organismo. Estes compostos não atuam de forma independente, mas sim por efeito aditivo, antagónico ou sinérgico, resultando numa interação dos vários constituintes e dos diversos locais de ação. Nos últimos anos ressurgiu o interesse por esta terapia nos países desenvolvidos, principalmente devido aos efeitos secundários que os medicamentos convencionais podem provocar, e também pelo uso descontrolado e abusivo de certos fármacos. Deste modo, o número de estudos científicos com plantas e seus compostos tem vindo a aumentar ao longo dos anos, fornecendo evidências científicas quanto à sua segurança, aceitabilidade, eficácia, e mostrando menos efeitos secundários que os medicamentos convencionais. Com este projeto pretende-se caraterizar o conhecimento e o consumo de fitoterápicos pela população do distrito de Viana do Castelo. Aplicou-se um estudo observacional, descritivo do tipo transversal e analítico. A população alvo do estudo é a população em geral, residente no distrito de Viana do Castelo, com mais de 18 anos de idade. Para a recolha de informação foi realizado um questionário anónimo, confidencial e voluntário, a 914 individuos. A amostra é constituída maioritariamente por indivíduos do género feminino (58,3%). A faixa etária mais frequente é dos 18 aos 25 anos (19,7%) distribuída por todos os concelhos do distrito. Verificou-se que mais de 40% da população tem doença crónica, e mais de 60% recorreu a produtos fitoterápicos no último ano, havendo uma relação entre quem recorre a esta terapia e a existência de uma patologia crónica associada. Observou-se ainda que mais da 80% da população que utiliza estes produtos se encontra satisfeita com os resultados, sendo que mais de 85% dos utilizadores de fitoterápicos pretende voltar a utilizá-los.

New analytical methodologies for doping control – detection of anabolic androgenic steroids in human urine

Dissertation submitted to Faculdade de Ciências e Tecnologia - Universidade Nova de Lisboa in fulfilment of the requirements for the degree of Doctor of Philosophy (Biochemistry - Biotechnology)

Avaliação da gestão da segurança do processo na central de ciclo combinado da Tapada do Outeiro e propostas de melhoria

A Gestão da Segurança do Processo consiste na implementação de procedimentos para controlar os perigos resultantes de fabrico, manuseamento e utilização de substâncias perigosas e da utilização de sistemas sob pressão em instalações industriais, pelo que se torna numa ferramenta de Gestão muito importante na indústria. Pela pesquisa realizada, a Gestão da Segurança do Processo é um tema pouco desenvolvido no nosso país, embora esteja diretamente relacionada com a Diretivas Seveso. Como colaborador da Central de Ciclo Combinado da Tapada do Outeiro, propus-me a avaliar a Gestão da Segurança do Processo na Central. A Direção da Central apoiou o tema, reservando a confidencialidade do trabalho final devido a assuntos sensíveis do negócio. Como resultado final do Projeto temos a avaliação da Gestão da Segurança do Processo na Central de Ciclo Combinado da Tapada do Outeiro, permitindo à gestão da Central identificar oportunidades para melhorar a efetividade do cumprimento deste objetivo.