Solubility of red 153 and blue 1 in supercritical carbon dioxide

Solubilities of red 153, (3-[[4-[[5,6(or 6,7)-dichloro-2-benzothiazolyl]azo]phenyl]ethylamino]propanenitrile), an azo compound, and disperse blue1 (1,4,5,8-tetraaminoantraquinone) in supercritical carbon dioxide (SC CO(2)) were measured at T = (333.2 to 393.2) K over the pressure range (12.0 to 40.0) MPa by a flow type apparatus. The solubility of red 153 (0.985. 10(-6) to 37.2. 10(-6)) in the overall region of measurements is found to be significantly higher than that of disperse blue 1 (1.12.10(-7) to 4.89.10(-7)). The solubility behavior of disperse red 153 follows the general solubility trend displayed by disperse dyes with a crossover pressure at about 20 MPa. On the other hand, blue 1, which is a disperse anthraquinone dye, exhibits unexpected behavior not recorded previously there is no crossover pressure at the temperature and pressure ranges studied, and the dye's solubility at T = 333.2 K practically does not increase with pressure. To the best of our knowledge, there are no previous measurements of blue 1 solubility in SC CO(2) reported in the literature. The experimental data were correlated by using the Soave Redlich Kwong equation of state (EoS) with the one-fluid van der Waals mixing rule, and an acceptable correlation of the solubility data for both dyes was obtained.

Osteometria radiográfica de fetos: contributo para a estimativa da idade à data da morte

A estimativa da idade gestacional em restos cadavéricos de fetos é importante em contextos forenses. Para esse efeito, os especialistas forenses recorrem à avaliação do padrão de calcificação dentária e/ou ao estudo do esqueleto. Neste último, o comprimento das diáfises de ossos longos é um dos métodos mais utilizados, sendo utilizadas tabelas e equações de regressão de obras pouco actuais ou baseadas em dados ecográficos, cujas medições diferem das efectuadas directamente no osso. Este trabalho tem como objectivo principal a construção de tabelas e equações de regressão para a população Portuguesa, com base na medição das diáfises de fémur, tíbia e úmero, utilizando radiografias post-mortem, que não diferem muito das medições em osso. Pretende-se também determinar qual dos três ossos é mais credível e se existem diferenças significativas entre fetos de género feminino e de género masculino.

Experimental Measurements and Correlation of the Solubility of Three Primary Amides in Supercritical CO2: Acetanilide, Propanamide, and Butanamide

Solubilities of three primary amides, namely, acetanilide, propanamide, and butanamide, in supercritical carbon dioxide were measured at T = (308.2, 313.2, and 323.2) K over the pressure range (9.0 to 40.0) MPa by a flow type apparatus. The solubility behavior of the three solids shows an analogous trend with a crossover region of the respective isotherms between (12 to 14) MPa. The solubility of each amide, at the same temperature and pressure, decreases from propanamide to acetanilide. Pure compound properties required for the modeling were estimated, and the solubilities of the amides were correlated by using the Soave-Redlich-Kwong cubic equation of state with an absolute average relative deviation (AARD) from (1.3 to 6.1) %.

Interpretation of gravity data to delineate structural features connected to low-temperature geothermal resources at Northeastern Portugal

A great number of low-temperature geothermal fields occur in Northern-Portugal related to fractured rocks. The most important superficial manifestations of these hydrothermal systems appear in pull-apart tectonic basins and are strongly conditioned by the orientation of the main fault systems in the region. This work presents the interpretation of gravity gradient maps and 3D inversion model produced from a regional gravity survey. The horizontal gradients reveal a complex fault system. The obtained 3D model of density contrast puts into evidence the main fault zone in the region and the depth distribution of the granitic bodies. Their relationship with the hydrothermal systems supports the conceptual models elaborated from hydrochemical and isotopic water analyses. This work emphasizes the importance of the role of the gravity method and analysis to better understand the connection between hydrothermal systems and the fractured rock pattern and surrounding geology. (c) 2013 Elsevier B.V. All rights reserved.

Classification and staging of chronic liver disease from multimodal data

Chronic liver disease (CLD) is most of the time an asymptomatic, progressive, and ultimately potentially fatal disease. In this study, an automatic hierarchical procedure to stage CLD using ultrasound images, laboratory tests, and clinical records are described. The first stage of the proposed method, called clinical based classifier (CBC), discriminates healthy from pathologic conditions. When nonhealthy conditions are detected, the method refines the results in three exclusive pathologies in a hierarchical basis: 1) chronic hepatitis; 2) compensated cirrhosis; and 3) decompensated cirrhosis. The features used as well as the classifiers (Bayes, Parzen, support vector machine, and k-nearest neighbor) are optimally selected for each stage. A large multimodal feature database was specifically built for this study containing 30 chronic hepatitis cases, 34 compensated cirrhosis cases, and 36 decompensated cirrhosis cases, all validated after histopathologic analysis by liver biopsy. The CBC classification scheme outperformed the nonhierachical one against all scheme, achieving an overall accuracy of 98.67% for the normal detector, 87.45% for the chronic hepatitis detector, and 95.71% for the cirrhosis detector.

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data

In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging.

Diffuse liver disease classification from ultrasound surface characterization, clinical and laboratorial data

In this work liver contour is semi-automatically segmented and quantified in order to help the identification and diagnosis of diffuse liver disease. The features extracted from the liver contour are jointly used with clinical and laboratorial data in the staging process. The classification results of a support vector machine, a Bayesian and a k-nearest neighbor classifier are compared. A population of 88 patients at five different stages of diffuse liver disease and a leave-one-out cross-validation strategy are used in the classification process. The best results are obtained using the k-nearest neighbor classifier, with an overall accuracy of 80.68%. The good performance of the proposed method shows a reliable indicator that can improve the information in the staging of diffuse liver disease.

Translation termination and protein folding pathway genes are not correlated in gastric cancer

Background: The eukaryotic release factor 3 (eRF3) has been shown to affect both tubulin and actin cytoskeleton, suggesting a role in cytoskeleton assembly, mitotic spindle formation and chromosome segregation. Also, direct interactions between eRF3 and subunits of the cytosolic chaperonin CCT have been described. Moreover, both eRF3a and CCT subunits have been described to be up-regulated in cancer tissues. Our aim was to evaluate the hypothesis that eRF3 expression levels are correlated with the expression of genes encoding proteins involved in the tubulin folding pathways. Methods: Relative expression levels of eRF1, eRF3a/GSPT1, PFDN4, CCT2, CCT4, and TBCA genes in tumour samples relative to their adjacent normal tissues were investigated using real time-polymerase chain reaction in 20 gastric cancer patients. Results: The expression levels of eRF3a/GSPT1 were not correlated with the expression levels of the other genes studied. However, significant correlations were detected between the other genes, both within intestinal and diffuse type tumours. Conclusions: eRF3a/GSPT1 expression at the mRNA level is independent from both cell translation rates and from the expression of the genes involved in tubulin-folding pathways. The differences in the patterns of expression of the genes studied support the hypothesis of genetically independent pathways in the origin of intestinal and diffuse type gastric tumours.

Magnesium, insulin resistance and body composition in healthy postmenopausal women

Objective: This study was conducted to determine the association between magnesium (Mg), body composition and insulin resistance in 136 sedentary postmenopausal women, 50 to 77 years of age. Methods: Diabetics, hypertensives and women on hormonal replacement therapy were excluded and the remaining 74 were divided according to BMI≥25 (obese: OG) and BMI<25 kg/m2 (non-obese: NOG). Nutritional data disclosed that intakes were high for protein and saturated fat, low for carbohydrates, polyunsaturated fat and Mg and normal for the other nutrients, according to recommended dietary allowances (RDA). Mg values in red blood cells (RBC-Mg) and plasma (P-Mg), were determined, as were fasting glucose, and insulin levels, Homeostasis Model Assessment (HOMA), body mass index (BMI), body fat percent (BF %), abdominal fat (AF) and free fat mass (FFM). Results: RBC-Mg values were low in both groups when compared with normal values. There were significant differences in body composition parameters, HOMA and insulin levels, with higher basal insulin levels in OG. RBC-Mg was directly correlated with insulin, HOMA and FFM in both groups, according to Pearson correlations. HOMA in OG was also directly correlated with BMI, FFM and AF. In NOG, HOMA was only correlated with FFM. The low RBC-Mg levels observed were probably due to low Mg intake and to deregulation of factors that control Mg homeostasis during menopause. Conclusions: Both Mg deficit and obesity may independently lead to a higher risk for insulin resistance and cardiovascular disease.

Endothelial lipase correlated positively with EPA/AA ratio in RBCs membrane

The fatty acid profile of erythrocyte membranes has been considered a good biomarker for several pathologic situations. Dietary intake, digestion, absorption, metabolism, storage and exchange amongst compartments, greatly influence the fatty acids composition of different cells and tissues. Lipoprotein and hepatic lipases were also involved in fatty acid availability. In the present work we examined the correlations between fatty acid in Red Blood Cells (RBCs) membranes, the fatty acid desaturase and elongase activities, glycaemia, blood lipids, lipoproteins and apoproteins, and the endothelial lipase (EL) mass in plasma. Twenty one individuals were considered in the present study, with age >18 y. RBCs membranes were obtained and analysed for fatty acid composition by gas chromatography. The amount of fatty acids (as percentage) were analysed, and the ratios between fatty acid 16:1/16:0; 18:1/18:0; 18:0/16:0; 22:6 n-3/20:5 n-3 and 20:4 n-6/18:2 n-6 were calculated. Bivariate analysis (rs) and partial correlations were determined. SCD16 estimation activity correlated positively with BMI (rs=0.466, p=0.043) and triacylglycerols (TAG) (rs=0.483, p=0.026), and negatively with the ratio ApoA1/ApoB (rs=-0.566, p=0.007). Endothelial lipase (EL) correlated positively with the EPA/AA ratio in RBCs membranes (rs=0.524, p=0.045). After multi-adjustment for BMI, age, hs-CRP and dietary n3/n6 ratio, the correlations remained significant between EL and EPA/AA ratio. At the best of our knowledge this is the first report that correlated EL with the fatty acid profile of RBCs plasma membranes. The association found here can suggest that the enzyme may be involved in the bioavailability and distribution of n-3/n-6 fatty acids, suggesting a major role for EL in the pathophysiological mechanisms involving biomembranes’ fatty acids, such as in inflammatory response and eicosanoids metabolites pathways.

Modelo de data mining para detecção de tumores em exames de rastreio

Dissertação para obtenção do grau de Mestre em Engenharia Informática

Modelo de data mining para deteção de embolias pulmonares

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Informática e de Computadores

Leptogenesis, CP violation and neutrino data: what can we learn?

A detailed analytic and numerical study of baryogenesis through leptogenesis is performed in the framework of the standard model of electroweak interactions extended by the addition of three right-handed neutrinos, leading to the seesaw mechanism. We analyze the connection between GUT-motivated relations for the quark and lepton mass matrices and the possibility of obtaining a viable leptogenesis scenario. In particular, we analyze whether the constraints imposed by SO(10) GUTs can be compatible with all the available solar, atmospheric and reactor neutrino data and, simultaneously, be capable of producing the required baryon asymmetry via the leptogenesis mechanism. It is found that the Just-So(2) and SMA solar solutions lead to a viable leptogenesis even for the simplest SO(10) GUT, while the LMA, LOW and VO solar solutions would require a different hierarchy for the Dirac neutrino masses in order to generate the observed baryon asymmetry. Some implications on CP violation at low energies and on neutrinoless double beta decay are also considered. (C) 2002 Elsevier Science B.V. All rights reserved.

Does independent component analysis play a role in unmixing hyperspectral data?

Independent component analysis (ICA) has recently been proposed as a tool to unmix hyperspectral data. ICA is founded on two assumptions: 1) the observed spectrum vector is a linear mixture of the constituent spectra (endmember spectra) weighted by the correspondent abundance fractions (sources); 2)sources are statistically independent. Independent factor analysis (IFA) extends ICA to linear mixtures of independent sources immersed in noise. Concerning hyperspectral data, the first assumption is valid whenever the multiple scattering among the distinct constituent substances (endmembers) is negligible, and the surface is partitioned according to the fractional abundances. The second assumption, however, is violated, since the sum of abundance fractions associated to each pixel is constant due to physical constraints in the data acquisition process. Thus, sources cannot be statistically independent, this compromising the performance of ICA/IFA algorithms in hyperspectral unmixing. This paper studies the impact of hyperspectral source statistical dependence on ICA and IFA performances. We conclude that the accuracy of these methods tends to improve with the increase of the signature variability, of the number of endmembers, and of the signal-to-noise ratio. In any case, there are always endmembers incorrectly unmixed. We arrive to this conclusion by minimizing the mutual information of simulated and real hyperspectral mixtures. The computation of mutual information is based on fitting mixtures of Gaussians to the observed data. A method to sort ICA and IFA estimates in terms of the likelihood of being correctly unmixed is proposed.