998 resultados para Mineral Favourability Index


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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.

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Mestrado em Engenharia Química – Ramo Optimização Energética na Indústria Química

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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.

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

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Business Strategy and the Environment nº 15, p. 71–86

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Dairy foods comprise a range of products with varying nutritional content. The intake of dairy products (DPs) has been shown to have beneficial effects on body weight and body fat. This study aimed to examine the independent association between DP intake, body mass index (BMI), and percentage body fat (%BF) in adolescents. A cross-sectional, school-based study was conducted with 1,001 adolescents (418 boys), ages 15–18 years, from the Azorean Archipelago, Portugal. Anthropometric measurements were recorded (weight and height), and %BF was assessed using bioelectric impedance analysis. Adolescent food intake was measured using a self-administered, semiquantitative food frequency questionnaire. Data were analyzed separately for girls and boys, and separate multiple linear regression analysis was used to estimate the association between total DP, milk, yogurt, and cheese intake, BMI, and %BF, adjusting for potential confounders. For boys and girls, respectively, total DP consumption was 2.6 ± 1.9 and 2.9 ± 2.5 servings/day (P = 0.004), while milk consumption was 1.7 ± 1.4 and 2.0 ± 1.7 servings/day (P = 0.001), yogurt consumption was 0.5 ± 0.6 and 0.4 ± 0.7 servings/day (P = 0.247), and cheese consumption was 0.4 ± 0.6 and 0.5 ± 0.8 servings/day (P = 0.081). After adjusting for age, birth weight, energy intake, protein, total fat, sugar, dietary fiber, total calcium intake, low-energy reporters, parental education, pubertal stage, and physical activity, only milk intake was negatively associated with BMI and %BF in girls (respectively, girls: β = −0.167, P = 0.013; boys: β = −0.019, P = 0.824 and girls: β = −0.143, P = 0.030; boys: β = −0.051, P = 0.548). Conclusion: We found an inverse association between milk intake and both BMI and %BF only in girls.

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The shifted Legendre orthogonal polynomials are used for the numerical solution of a new formulation for the multi-dimensional fractional optimal control problem (M-DFOCP) with a quadratic performance index. The fractional derivatives are described in the Caputo sense. The Lagrange multiplier method for the constrained extremum and the operational matrix of fractional integrals are used together with the help of the properties of the shifted Legendre orthonormal polynomials. The method reduces the M-DFOCP to a simpler problem that consists of solving a system of algebraic equations. For confirming the efficiency and accuracy of the proposed scheme, some test problems are implemented with their approximate solutions.

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Thick smears of human feces can be made adequate for identification of helminth eggs by means of refractive index matching. Although this effect can be obtained by simply spreading a fleck of feces on a microscope slide, a glycerol solution has been routinely used to this end. Aiming at practicability, a new quantitative technique has been developed. To enhance both sharpness and contrast of the images, a sucrose solution (refractive index = 1.49) is used, which reduces the effect of light-scattering particulates. To each slide a template-measured (38.5 mm³) fecal sample is transferred. Thus, egg counts and sensitivity evaluations are easily made.

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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.

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The sylvatic triatomine Rhodnius pallescens is considered to be the most important and widespread vector of Trypanosoma cruzi and Trypanosoma rangeli in Panama. However, its behavior and biological characteristics have only been partially investigated. Thus, to achieve sustainable and efficient control over Chagas disease in Panama, a better understanding of the ecology and biology of R. pallescens is essential. In this study we evaluated R. pallescens host feeding sources using a dot-blot assay, and the trypanosome infection index by PCR analysis in a Chagas disease endemic area of central Panama. It was found that in peridomestic palm trees, 20.3% of the examined bugs had fed on opossums (Didelphis marsupialis). However, we observed an increased anthropophagy (25.4%) for those bugs collected inside houses. Considering the domestic and peridomestic habitats as a whole, the proportion of collected R. pallescens infected with trypanosomes was 87.4%. In the two habitats the predominant infection was with T. cruzi (80-90%). Between 47-51% of the analyzed triatomines were infected with T. rangeli. Mixed infections (40-51%) were also detected. These findings provide a better basis for the implementation of a rational control and surveillance program for Chagas disease in regions where R. pallescens is endemic.

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Objective: Localizing epileptic foci in posterior brain epilepsy remains a difficult exercise in surgery for epilepsy evaluation. Neither clinical manifestations, neurological, EEG nor neuropsychological evaluations provide strong information about the area of onset, and fast spread of paroxysms often produces mixed features of occipital, temporal and parietal symptoms. We investigated the usefulness of the N170 event-related potential to map epileptic activity in these patients. Methods: A group of seven patients with symptomatic posterior cortex epilepsy were submitted to a high-resolution EEG (78 electrodes), with recordings of interictal spikes and face-evoked N170. Generators of spikes and N170 were localized by source analysis. Range of normal N170 asymmetry was determined in 30 healthy volunteers. Results: In 3 out of 7 patients the N170 inter-hemispheric asymmetry was outside control values. Those were the patients whose spike sources were nearest (within 3 cm) to the fusiform gyrus, while foci further away did not affect the N170 ratio. Conclusions: N170 event-related potential provides useful information about focal cortical dysfunction produced by epileptic foci located in the close neighborhood of the fusiform gyrus, but are unaffected by foci further away. Significance: The N170 evoked by faces can improve the epileptic foci localization in posterior brain epilepsy.

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We used a prospective cohort to analyze the effect of change in BMI rather than change in weight, in mothers carrying dichorionic twins from a population that did not receive any dietary intervention. A total of 269 mothers (150 nulliparas and 119 multiparas) were evaluated. The average change (%) from the pre-gravid BMI was 7.2+/-6.1, 17.4+/-8.2, and 28.7+/-10.8, at 12-14, 22-25, and 30-34 weeks, respectively, without difference between nulliparas and multiparas. The comparison between maternities below or above the average change from the pregravid BMI failed to demonstrate an advantage (in terms of total twin birthweight and gestational age) of an above average change from the pregravid BMI, even when the lower versus upper quartiles were compared. Our observations reached different conclusions regarding the recommended universal dietary intervention in twin gestations. A cautious approach is advocated towards seemingly harmless excess weight gain, as normal weight women may turn overweight, or even obese, by the end of pregnancy, and be exposed to the untoward effects of obesity on future health and body image.

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Este trabalho pretende estabelecer uma relação entre o Work Index e algumas propriedades das rochas. Através da pesquisa bibliográfica foram identificadas varias propriedades com possível influência no valor do Work Index, das quais foram seleccionadas a massa volúmica aparente, a resistência à carga pontual, a composição química, a composição mineralógica e a abrasividade. Adicionalmente a porosidade aberta e resistência à compressão também foram analisadas. Assim foram analisadas 10 amostras de rocha, quatro de granitos, uma de quartzodiorito, uma de ardósia, uma de serpentinito, uma de calcário, uma de mármore e uma de sienito nefelínico, sobre as quais já eram conhecidos os valores de cinco das propriedades referidas previamente, tendo sido determinados os valores das ainda desconhecidas, resistência à carga pontual e a abrasividade que está representada através do resultado do ensaio capon. Devido à dificuldade de execução do ensaio de determinação do Work Index de Bond foram recolhidos dados bibliográficos de valores do Work Index para as amostras de rocha seleccionadas e adoptado o valor médio para cada uma. Os dados obtidos foram tratados estatisticamente através do método de análise de componentes principais assim como através de regressões lineares simples e múltiplas. A análise de componentes principais permitiu identificar várias propriedades da rocha com possível influência sobre o Work Index de entre as analisadas. Foi possível estabelecer uma relação entre o Work Index e quatro das propriedades seleccionadas, designadamente a porosidade aberta, a resistência à compressão, a resistência à carga pontual e a abrasividade.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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Introduction: Highly Active Antiretroviral Therapy (HAART) has improved and extended the lives of thousands of people living with HIV/AIDS around the world. However, this treatment can lead to the development of adverse reactions such as lipoatrophy/lipohypertrophy syndrome (LLS) and its associated risks. Objective: This study was designed to assess the prevalence of self-reported lipodystrophy and nutritional status by anthropometric measurements in patients with HIV/AIDS. Methods: An observational study of 227 adult patients in the Secondary Immunodeficiencies Outpatient Department of Dermatology, Hospital das Clínicas, Faculty of Medicine, University of São Paulo (3002 ADEE-HCFMUSP). The sample was divided into three groups; Group 1 = 92 patients on HAART and with self-reported lipodystrophy, Group 2 = 70 patients on HAART without self-reported lipodystrophy and Group 3 = 65 patients not taking HAART. The nutritional status of individuals in the study sample was determined by body mass index (BMI) and percentage of body fat (% BF). The cardiovascular risk and diseases associated with abdominal obesity were determined by waist/hip ratio (WHR) and waist circumference (WC). Results: The prevalence of self-reported lipoatrophy/lipohypertrophy syndrome was 33% among women and 59% among men. Anthropometry showed depletion of fat mass in the evaluation of the triceps (TSF) in the treatment groups with HAART and was statistically independent of gender; for men p = 0.001, and for women p = 0.007. Similar results were found in the measurement of skin folds of the upper and lower body (p = 0.001 and p = 0.003 respectively). In assessing the nutritional status of groups by BMI and % BF, excess weight and body fat were more prevalent among women compared to men (p = 0.726). The WHR and WC revealed risks for cardiovascular and other diseases associated with abdominal obesity for women on HAART and with self-reported LLS (p = 0.005) and (p = 0.011). Conclusions: Anthropometric measurements were useful in the confirmation of the prevalence of LLS. BMI alone does not appear to be a good parameter for assessing the nutritional status of HIV-infected patients on HAART and with LLS. Other anthropometric measurements are needed to evaluate patients with the lipoatrophy/lipohypertrophy syndrome.