Implementation of a new reference values database for semiquantification in123I-FP-CIT brain single emission tomography

Brain dopamine transporters imaging by Single Emission Tomography (SPECT) with 123I-FP-CIT (DaTScanTM) has become an important tool in the diagnosis and evaluation of Parkinson syndromes.This diagnostic method allows the visualization of a portion of the striatum – where healthy pattern resemble two symmetric commas - allowing the evaluation of dopamine presynaptic system, in which dopamine transporters are responsible for dopamine release into the synaptic cleft, and their reabsorption into the nigrostriatal nerve terminals, in order to be stored or degraded. In daily practice for assessment of DaTScan TM, it is common to rely only on visual assessment for diagnosis. However, this process is complex and subjective as it depends on the observer’s experience and it is associated with high variability intra and inter observer. Studies have shown that semiquantification can improve the diagnosis of Parkinson syndromes. For semiquantification, analysis methods of image segmentation using regions of interest (ROI) are necessary. ROIs are drawn, in specific - striatum - and in nonspecific – background – uptake areas. Subsequently, specific binding ratios are calculated. Low adherence of semiquantification for diagnosis of Parkinson syndromes is related, not only with the associated time spent, but also with the need of an adapted database of reference values for the population concerned, as well as, the examination of each service protocol. Studies have concluded, that this process increases the reproducibility of semiquantification. The aim of this investigation was to create and validate a database of healthy controls for Dopamine transporters with DaTScanTM named DBRV. The created database has been adapted to the Nuclear Medicine Department’s protocol, and the population of Infanta Cristina’s Hospital located in Badajoz, Spain.

Validation of a new reference values’s database for semiquantification of 123I‐FP‐CIT SPECT scans in one nuclear medicine department

The DatScanTM and its Semiquantification (SQ) can provide advantages in the diagnosis of Parkinsonian Syndromes (PS). To improve the SQ is recommended the creation of adapted database (DB) with reference values for the Nuclear Medicine Departments. Previously to this work was created a adapted database (DBRV) to Nuclear Medicine Department's protocol and population of Infanta Cristina's Hospital located in Badajoz, for patients between the ages of 60 and 75, and reference values of the SQ were calculated. Aim: To evaluate the discrimination capacity of a department's adapted DB reference's values of healthy controls for DatScanTM.

Clinical classification versus semiquantification with adapted reference values for 123I-FP-CIT SPECT in a nuclear medicine department

Semi quantification (SQ) in DaTScan® studies is broadly used in clinic daily basis, however there is a suspicious about its discriminative capability, and concordance with the diagnostic classification performed by the physician. Aim: Evaluate the discriminate capability of an adapted database and reference's values of healthy controls for the Dopamine Transporters (DAT) with 123I–FP-IT named DBRV adapted to Nuclear Medicine Department's protocol and population of Infanta Cristina's Hospital, and its concordance with the physician classification.

Predictive value of serologic tests in the diagnosis and follow-up of patients with paracoccidioidomycosis

A serologic study was undertaken in a group of 43 patients with active paracoccidioidomycosis who were treated in the same form (ketoconazole), for identical periods of time (6 months), and folio wed-up for various periods posttherapy. The tests employed were agar gel immunodiffusion (AGID) and complement fixation (FC). Also studied were 50 sera from patients with proven histoplasmosis and pulmonary aspergilloma, 30 patients with culturaly proven tuberculosis as well as 92 specimens from healthy individuals, residents in the endemic area for paracoccidioidomycosis. A single lot of yeast filtrate antigen was used throughout the study. The value of each test was measured according to GALEN and GAMBINO6. Both tests were highly sensitive, 89 and 93% respectively. Regarding their specificity, the AGID was totally specific while the CF exhibited 96.6% and 97% specificity in front of tuberculosis patients and healthy individuals respectively and 82% in comparison with patients with other mycoses. The concept of predictive value, that is, the certainty one has in accepting a positive test as diagnostic of paracoccidioidomycosis, favored the AGID procedure (100%) over the CF test. The latter could sort out with 93% certainty a patient with paracoccidioidomycosis among a group of healthy individuals and with 97.5% in the case of TB patients; when the group in question was composed by individuals with other deep mycoses, such certainty was lower (81%). The above results indicate that both the AGID and the CF tests furnish results of high confidence; one should not relay, however, in the CF alone as a means to establish the specific diagnosis of paracoccidioidomycosis.

Controlo da fermentação do mosto e das condições ambientais de uma sala de lagares

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Digitally programmable delay-locked-loop with adaptive charge pump current for UWB radar system

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e Computadores

O auditor interno e a gestão do risco empresarial

O objetivo central deste estudo consiste em demonstrar de que forma o trabalho do auditor interno contribui no processo de gestão de riscos empresariais. Neste sentido, faz-se uma abordagem sobre o conceito de Auditoria Interna, sendo uma atividade destinada a acrescentar valor à organização na medida em que a auxilia na consecução dos seus objetivos, proporcionando-lhe informações oportunas e relevantes para a tomada de decisão. Faz também considerações ao Controlo Interno, no sentido de que as organizações vão sentir diferentes necessidades de controlo interno dependendo da sua dimensão e complexidade do negócio. O controlo interno é um processo desenvolvido pelos Orgãos de Gestão com o propósito de garantir uma segurança razoável no cumprimento dos objetivos estabelecidos. Cabe ao auditor interno auxiliar nesse sentido, ou seja, debruçar-se sobre a avaliação da adequação e eficiência do Sistema de Controlo Interno. Por fim é abordada a importância da Gestão do Risco, neste contexto as organizações têm como compromisso prioritário a implementação de mecanismos de avaliação e gestão dos riscos que possam afetar as suas operações e o cumprimento dos objetivos estratégicos definidos. A Auditoria Interna vai fornecer segurança acerca da eficácia das atividades de gestão do risco das organizações para assegurar que os principais riscos de negócio estão a ser geridos de forma apropriada bem como os sistemas de controlo interno estão a funcionar eficazmente. Ainda na gestão do risco é abordado o modelo COSO ERM, instrumento importante para as organizações na medida em que melhoram a performance e o desempenho dos controlos internos implementados e progridem para um processo de gestão do risco. Faz-se também uma breve referência sobre a Lei Sox, que veio promover uma profunda reforma na elaboração dos relatórios financeiros, no detalhe minucioso sobre os aspetos do controlo interno nas organizações e na transparência das informações divulgadas pelas organizações.

Effect of peel and seed removal on the nutritional value and antioxidant activity of tomato (Lycopersicon esculentum L.) fruits

The effect of peel and seed removal, two commonly practiced procedures either at home or by the processing industry, on the physicochemical properties, bioactive compounds contents and antioxidant capacity of tomato fruits of four typical Portuguese cultivars (cereja, chucha, rama and redondo) were appraised. Both procedures caused significant nutritional and antioxidant activity losses in fruits of every cultivar. In general, peeling was more detrimental, since it caused a higher decrease in lycopene, bcarotene, ascorbic acid and phenolics contents (averages of 71%, 50%, 14%, and 32%, respectively) and significantly lowered the antioxidant capacity of the fruits (8% and 10%, using DPPH. and b-carotene linoleate model assays, correspondingly). Although seeds removal favored the increase of both color and sweetness, some bioactive compounds (11% of carotenoids and 24% of phenolics) as well as antioxidant capacity (5%) were loss. The studied cultivars were differently influenced by these procedures. The fruits most affected by peeling were those from redondo cultivar (-66% lycopene, -44% b-carotene, -26% ascorbic acid and -38% phenolics). Seeds removal, in turn, was more injurious for cereja tomatoes (-10% lycopene, -38% b-carotene, -25% ascorbic acid and -63% phenolics). Comparatively with the remaining ones, the rama fruits were less affected by the trimming procedures.

Multi-elemental analysis of ready-to-eat “baby leaf” vegetables using microwave digestion and high-resolution continuum source atomic absorption spectrometry

The mineral content (phosphorous (P), potassium (K), sodium (Na), calcium (Ca), magnesium (Mg), iron (Fe), manganese (Mn), zinc (Zn) and copper (Cu)) of eight ready-to-eat baby leaf vegetables was determined. The samples were subjected to microwave-assisted digestion and the minerals were quantified by High-Resolution Continuum Source Atomic Absorption Spectrometry (HR-CS-AAS) with flame and electrothermal atomisation. The methods were optimised and validated producing low LOQs, good repeatability and linearity, and recoveries, ranging from 91% to 110% for the minerals analysed. Phosphorous was determined by a standard colorimetric method. The accuracy of the method was checked by analysing a certified reference material; results were in agreement with the quantified value. The samples had a high content of potassium and calcium, but the principal mineral was iron. The mineral content was stable during storage and baby leaf vegetables could represent a good source of minerals in a balanced diet. A linear discriminant analysis was performed to compare the mineral profile obtained and showed, as expected, that the mineral content was similar between samples from the same family. The Linear Discriminant Analysis was able to discriminate different samples based on their mineral profile.

Calcareous nannofossil assemblages around the Pliensbachian/Toarcian boundary in the reference section of Peniche (Portugal)

The Pliensbachian/Toarcian boundary (Lower Jurassic) is well represented in the Lusitanian Basin (Portugal), mainly in the Peniche area, recorded by a marl/limestone series. Calcareous nannofossil assemblages are described herein, with the aim to contribute to the Toarcian GSSP definition. Marly samples were collected 3 m below and 7 m above this boundary and analysed for calcareous nannofossils. The main nannofossils observed were Biscutum finchii, B. grande, Calcivascularis jansae, Crepidolithus crassus, C. granulatus, C. impontus, Lotharingius hauffii, L. sigillatus, L. aff. L. velatus, Schizosphaerella spp. and Tubirhabdus patulus. This assemblage indicates that the Pliensbachian/Toarcian boundary in Peniche lies in the upper part of the NJ5b Subzone. Schizosphaerella and Lotharingius dominate the assemblage. The abundant occurrence of C. jansae and the common occurrence of B. grande indicate a strong Tethyan influence.

Acção do vento em pontes: estudo comparativo RSA/NP EN 1991-1-4

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização em Estruturas

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.

Simulação de um processo de pirólise rápida de biomassa

Mestrado em Engenharia Química - Ramo Optimização Energética na Indústria Química

The value of adenosine deaminase (ADA) determination in the diagnosis of tuberculous ascites

In order to evaluate the role of the determination of adenosine deaminase activity (ADA) in ascitic fluid for the diagnosis of tuberculosis, 44 patients were studied. Based on biochemical, cytological, histopathological and microbiological tests, the patients were divided into 5 groups: G1 - tuberculous ascites (n = 8); G2 - malignant ascites (n = 13); G3 - spontaneous bacterial peritonitis (n = 6); G4 - pancreatic ascites (n = 2); G5 - miscelaneous ascites (n = 15). ADA concentration were significantly higher in G1 (133.50 ± 24.74 U/l) compared to the other groups (G2 = 41.85 ± 52.07 U/l; G3 = 10.63 ± 5.87 U/l; G4 = 18.00 ± 7.07 U/l; G5 = 11.23 ± 7.66 U/l). At a cut-off value of >31 U/l, the sensitivity, specificity and positive and negative preditive values were 100%, 92%, 72% and 100%, respectively. ADA concentrations as high as in tuberculous ascites were only found in two malignant ascites caused by lymphoma. We conclude that ADA determination in ascitic fluid is a useful and reliable screening test for diagnosing tuberculous ascites. Values of ADA higher than 31 U/l indicate more invasive methods to confirm the diagnosis of tuberculosis.