Commercial squids: Characterization, assessment of potential health benefits/risks and discrimination based on mineral, lipid and vitamin E concentrations

The most consumed squid species worldwide were characterized regarding their concentrations of minerals, fatty acids, cholesterol and vitamin E. Interspecific comparisons were assessed among species and geographical origin. The health benefits derived from squid consumption were assessed based on daily minerals intake and on nutritional lipid quality indexes. Squids contribute significantly to daily intake of several macro (Na, K, Mg and P) and micronutrients (Cu, Zn and Ni). Despite their low fat concentration, they are rich in long-chain omega-3 fatty acids, particularly docosahexaenoic (DHA) and eicosapentanoic (EPA) acids, with highly favorable ω-3/ω-6 ratios (from 5.7 to 17.7), reducing the significance of their high cholesterol concentration (140–549 mg/100 g ww). Assessment of potential health risks based on minerals intake, non-carcinogenic and carcinogenic risks indicated that Loligo gahi (from Atlantic Ocean), Loligo opalescens (from Pacific Ocean) and Loligo duvaucelii (from Indic Ocean) should be eaten with moderation due to the high concentrations of Cu and/or Cd. Canonical discriminant analysis identified the major fatty acids (C14:0, C18:0, C18:1, C18:3ω-3, C20:4ω-6 and C22:5ω-6), P, K, Cu and vitamin E as chemical discriminators for the selected species. These elements and compounds exhibited the potential to prove authenticity of the commercially relevant squid species.

Large-area homogeneous periodic surface structures generated on the surface sputtered boron carbide thin films by femtosecond laser processing

Amorphous and crystalline sputtered boron carbide thin films have a very high hardness even surpassing that of bulk crystalline boron carbide (≈41 GPa). However, magnetron sputtered B-C films have high friction coefficients (C.o.F) which limit their industrial application. Nanopatterning of materials surfaces has been proposed as a solution to decrease the C.o.F. The contact area of the nanopatterned surfaces is decreased due to the nanometre size of the asperities which results in a significant reduction of adhesion and friction. In the present work, the surface of amorphous and polycrystalline B-C thin films deposited by magnetron sputtering was nanopatterned using infrared femtosecond laser radiation. Successive parallel laser tracks 10 μm apart were overlapped in order to obtain a processed area of about 3 mm2. Sinusoidal-like undulations with the same spatial period as the laser tracks were formed on the surface of the amorphous boron carbide films after laser processing. The undulations amplitude increases with increasing laser fluence. The formation of undulations with a 10 μm period was also observed on the surface of the crystalline boron carbide film processed with a pulse energy of 72 μJ. The amplitude of the undulations is about 10 times higher than in the amorphous films processed at the same pulse energy due to the higher roughness of the films and consequent increase in laser radiation absorption. LIPSS formation on the surface of the films was achieved for the three B-C films under study. However, LIPSS are formed under different circumstances. Processing of the amorphous films at low fluence (72 μJ) results in LIPSS formation only on localized spots on the film surface. LIPSS formation was also observed on the top of the undulations formed after laser processing with 78 μJ of the amorphous film deposited at 800 °C. Finally, large-area homogeneous LIPSS coverage of the boron carbide crystalline films surface was achieved within a large range of laser fluences although holes are also formed at higher laser fluences.

Preliminary study on the production of functionally graded materials by friction stir processing

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

4Sensing - decentralized processing for participatory sensing data

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática.

Processing and characterization of 3D dense chitosan pieces, for orthopedic applications, by adding plasticizers

In this work, plasticizer agents were incorporated in a chitosan based formulation, as a strategy to improve the fragile structure of chitosan based-materials. Three different plasticizers: ethylene glycol, glycerol and sorbitol, were blended with chitosan to prepare 3D dense chitosan specimens. The properties of the obtained structures were assessed for mechanical, microstructural, physical and biocompatibility behavior. The results obtained revealed that from the different specimens prepared, the blend of chitosan with glycerol has superior mechanical properties and good biological behavior, making this chitosan based formulation a good candidate to improve robust chitosan structures for the construction of bioabsorbable orthopedic implants.

Teor mineral e capacidade antioxidante em chás e infusões

Mestrado em Engenharia Química – Ramo Optimização Energética na Indústria Química

Advanced image processing techniques for detection and quantification of drusen

Dissertation presented to obtain the degree of Doctor of Philosophy in Electrical Engineering, speciality on Perceptional Systems, by the Universidade Nova de Lisboa, Faculty of Sciences and Technology

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.

Downstream processing development of enveloped viruses for clinical applications: innovative tools for rational process optimization

Dissertation presented to obtain a Ph.D. degree in Engineering and Technology Sciences, Biotechnology at the Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa

Aplicação dos sistemas de informação geográfica ao sector mineral: caso de estudo – região da Jamba - Angola

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica.

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.

Effects of storage, processing and proteolytic digestion on microcystin-LR concentration in edible clams

Accumulation of microcystin-LR (MC-LR) in edible aquatic organisms, particularly in bivalves, is widely documented. In this study, the effects of food storage and processing conditions on the free MC-LR concentration in clams (Corbicula fluminea) fed MC-LR-producing Microcystisaeruginosa (1 × 105 cell/mL) for four days, and the bioaccessibility of MC-LR after in vitro proteolytic digestion were investigated. The concentration of free MC-LR in clams decreased sequentially over the time with unrefrigerated and refrigerated storage and increased with freezing storage. Overall, cooking for short periods of time resulted in a significantly higher concentration (P < 0.05) of free MC-LR in clams, specifically microwave (MW) radiation treatment for 0.5 (57.5%) and 1 min (59%) and boiling treatment for 5 (163.4%) and 15 min (213.4%). The bioaccessibility of MC-LR after proteolytic digestion was reduced to 83%, potentially because of MC-LR degradation by pancreatic enzymes. Our results suggest that risk assessment based on direct comparison between MC-LR concentrations determined in raw food products and the tolerable daily intake (TDI) value set for the MC-LR might not be representative of true human exposure.

The Crystal Structure of the Escherichia coli Autoinducer-2 Processing Protein LsrF

PLOS ONE, 4(8):ARTe6820

Espresso beverages of pure origin coffee: Mineral characterization, contribution for mineral intake and geographical discrimination

Espresso coffee beverages prepared from pure origin roasted ground coffees from the major world growing regions (Brazil, Ethiopia, Colombia, India, Mexico, Honduras, Guatemala, Papua New Guinea, Kenya, Cuba, Timor, Mussulo and China) were characterized and compared in terms of their mineral content. Regular consumption of one cup of espresso contributes to a daily mineral intake varying from 0.002% (sodium; Central America) to 8.73% (potassium; Asia). The mineral profiles of the espresso beverages revealed significant inter- and intra-continental differences. South American pure origin coffees are on average richer in the analyzed elements except for calcium, while samples from Central America have generally lower mineral amounts (except for manganese). Manganese displayed significant differences (p < 0.05) among the countries of each characterized continent. Intercontinental and inter-country discrimination between the major world coffee producers were achieved by applying canonical discriminant analysis. Manganese and calcium were found to be the best chemical descriptors for origin.

Effects of tissue handling and processing steps on PCR for detection of Mycobacterium tuberculosis in formalin-fixed paraffin-embedded samples

Development and standardization of reliable methods for detection of Mycobacterium tuberculosis in clinical samples is an important goal in laboratories throughout the world. In this work, lung and spleen fragments from a patient who died with the diagnosis of miliary tuberculosis were used to evaluate the influence of the type of fixative as well as the fixation and paraffin inclusion protocols on PCR performance in paraffin embedded specimens. Tissue fragments were fixed for four h to 48 h, using either 10% non-buffered or 10% buffered formalin, and embedded in pure paraffin or paraffin mixed with bee wax. Specimens were submitted to PCR for amplification of the human beta-actin gene and separately for amplification of the insertion sequence IS6110, specific from the M. tuberculosis complex. Amplification of the beta-actin gene was positive in all samples. No amplicons were generated by PCR-IS6110 when lung tissue fragments were fixed using 10% non-buffered formalin and were embedded in paraffin containing bee wax. In conclusion, combined inhibitory factors interfere in the detection of M. tuberculosis in stored material. It is important to control these inhibitory factors in order to implement molecular diagnosis in pathology laboratories.