Análise comparativa de soluções adotadas para a reabilitação de pavimentos flexíveis que integram a rede rodoviária nacional

A presente dissertação tem como objetivo efetuar a análise comparativa de soluções adotadas de reabilitação de pavimentos flexíveis que integram a rede rodoviária nacional. No âmbito desta análise apresenta-se o estado da arte respeitante à reabilitação de pavimentos flexíveis, nomeadamente: mecanismos de degradação, famílias de degradações, avaliação da capacidade de carga dos pavimentos, metodologia utilizada no dimensionamento do reforço de pavimentos, sendo também efetuada uma análise comparativa de técnicas de reforço de pavimentos e dos tratamentos antifendas. Neste contexto, apresenta-se um caso de estudo no qual é efetuada uma análise de três soluções possíveis para a reabilitação estrutural do pavimento do IC 20 entre Almada e a Costa de Caparica. É feita a descrição da solução projetada pela EP, SA patenteada em concurso público lançado em 2007, a qual é de certa forma inovadora ao nível do tratamento retardador da reflexão de fendas. Aquela solução técnica é constituída pela aplicação de grelhas de fibra de vidro e grelhas de fibra de carbono, seguidas da colocação de uma camada de desgaste em mistura betuminosa rugosa com betume modificado com baixa percentagem de borracha reciclada de pneus usados (BBr - BBB). Complementarmente, é efetuada a análise da solução do projeto de reabilitação do IC 20, patenteado pela Subconcessionária do Baixo Tejo, que contemplou a aplicação de misturas betuminosas rugosas com betume modificado com média percentagem de borracha reciclada de pneus usados (BBr - BBM). Para além da solução patenteada pela subconcessionária, é analisada a solução do projeto de alterações (variante) apresentado pelo agrupamento de empresas construtoras, que foi adotado na execução da obra realizada no IC 20. A intervenção de reabilitação estrutural contemplou a utilização de uma camada de ligação em AC 16 10/20 (MBAM) e uma camada de desgaste em mistura betuminosa rugosa com betume modificado com média percentagem de borracha reciclada de pneus usados (BBr - BBM). Adicionalmente à caracterização de diferentes soluções de reabilitação de pavimentos flexíveis adotados em Portugal, é efetuada uma análise comparativa dos custos de ciclo de vida (construção, manutenção e conservação) de cada tipo de solução de reabilitação.

Arrow Plot: a new graphical tool for selecting up and down regulated genes and genes differentially expressed on samples subgroups

Background: A common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software. Results: This method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes. Conclusion: Our results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.

Waste Marble Dust Blended Cement

Marble processing activities generates a.significant amount of waste in dust form. This waste, which is nowadays one of the environmental problems worldwide, presents great potential of being used as mineral addition in blended cements production. This paper shows preliminary results of an ongoing project which ultimate goal is to investigate the viability of using waste marble dust (WMD), produced by marble Portuguese industry, as cement replacement material. In order to evaluate the effects of the WMD on mechanical behaviour, different mortar blended cement mixtures were tested. These mixtures were prepared with different partial substitution level of cement with WMD. Strength results of WMD blended cements were compared to control cements with same level of incorporation of natural limestone used to produce commercial Portland-limestone cements. The results obtained show that WMD blended cements perform better than limestone blended cements for same replacement level up to 20% w/w. Therefore, WMD reveals promising attributes for blended cements production.

Assessment of saccharide fractionation by ultrafiltration and nanofiltration

This paper addresses the investigation of the fractionation of saccharide mixtures and saccharide mixtures with calcium using ultrafiltration (UF) and nanofiltration (NF). A set of cellulose acetate membranes covered a wide range of molecular weight cut-off (MWCO) ranging from 250 to 46,000 Da and the total feed concentration of saccharides mixtures varied from 1550 to 4700 ppm with the ratio of the two saccharides-solutes (glucose to raffinose) being kept constant at the value of 1.8. The evolution pattern of the saccharide concentration ratio in the UF/NF permeate streams displayed a dependence on the membrane MWCO, on the total sugar concentration and on the presence of calcium ions. For the highest total sugar content, the membranes with MWCO from 2000 to 7000 Da showed saccharide fractionation capability that was enhanced in the presence of calcium. The Steric Pore Flow Model was used to predict individual solute permeation behaviours and to assess the deviations to steric hindered transport of the solutes in multi-component saccharide solutions. (C) 2008 Elsevier B.V. All rights reserved.

Solution enthalpies of 1,4-dioxane: Study of solvent effects through quantitative structure-property relationships

Solution enthalpies of 1,4-dioxane have been obtained in 15 protic and aprotic solvents at 298.15 K. Breaking the overall process through the use of Solomonov's methodology the cavity term was calculated and interaction enthalpies (Delta H-int) were determined. Main factors involved in the interaction enthalpy have been identified and quantified using a QSPR approach based on the TAKA model equation. The relevant descriptors were found to be pi* and beta, which showed, respectively, exothermic and endothermic contributions. The magnitude of pi* coefficient points toward non-specific solute-solvent interactions playing a major role in the solution process. The positive value of the beta coefficient reflects the endothermic character of the solvents' hydrogen bond acceptor (HBA) basicity contribution, indicating that solvent molecules engaged in hydrogen bonding preferentially interact with each other rather than with 1,4-dioxane. (C) 2013 Elsevier B.V. All rights reserved.

Capillary bridging and long-range attractive forces in a mean-field approach

When a mixture is confined, one of the phases can condense out. This condensate, which is otherwise metastable in the bulk, is stabilized by the presence of surfaces. In a sphere-plane geometry, routinely used in atomic force microscope and surface force apparatus, it, can form a bridge connecting the surfaces. The pressure drop in the bridge gives rise to additional long-range attractive forces between them. By minimizing the free energy of a binary mixture we obtain the force-distance curves as well as the structural phase diagram of the configuration with the bridge. Numerical results predict a discontinuous transition between the states with and without the bridge and linear force-distance curves with hysteresis. We also show that similar phenomenon can be observed in a number of different systems, e.g., liquid crystals and polymer mixtures. (C). 2004 American Institute of Physics.

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.

Dependent component analysis: a hyperspectral unmixing algorithm

Linear unmixing decomposes a hyperspectral image into a collection of reflectance spectra of the materials present in the scene, called endmember signatures, and the corresponding abundance fractions at each pixel in a spatial area of interest. This paper introduces a new unmixing method, called Dependent Component Analysis (DECA), which overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical properties of hyperspectral data. DECA models the abundance fractions as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. The performance of the method is illustrated using simulated and real data.

Does Independent Component Analysis Play a Role in Unmixing Hyperspectral Data?

Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings

Demixing instability in coil-rod blends undergoing polycondensation reactions

The authors extend their earlier work on the stability of a reacting binary polymer blend with respect to demixing [D. J. Read, Macromolecules 31, 899 (1998); P. I. C. Teixeira , Macromolecules 33, 387 (2000)] to the case where one of the polymers is rod-like and may order nematically. As before, the authors combine the random phase approximation for the free energy with a Markov chain model for the chemistry to obtain the spinodal as a function of the relevant degrees of reaction. These are then calculated by assuming a simple second-order chemical kinetics. Results are presented, for linear systems, which illustrate the effects of varying the proportion of coils and rods, their relative sizes, and the strength of the nematic interaction between the rods. (c) 2007 American Institute of Physics.

Characterization of airborne particles generated from metal active gas welding process

This study is focused on the characterization of particles emitted in the metal active gas welding of carbon steel using mixture of Ar + CO2, and intends to analyze which are the main process parameters that influence the emission itself. It was found that the amount of emitted particles (measured by particle number and alveolar deposited surface area) are clearly dependent on the distance to the welding front and also on the main welding parameters, namely the current intensity and heat input in the welding process. The emission of airborne fine particles seems to increase with the current intensity as fume-formation rate does. When comparing the tested gas mixtures, higher emissions are observed for more oxidant mixtures, that is, mixtures with higher CO2 content, which result in higher arc stability. These mixtures originate higher concentrations of fine particles (as measured by number of particles by cm 3 of air) and higher values of alveolar deposited surface area of particles, thus resulting in a more severe worker's exposure.

Biomonitorization in hospital settings with cytostatics occupational exposure

Exposure in a hospital setting is normally due to the use of several antineoplastic drugs simultaneously. Nevertheless, the effects of such mixtures at the cell level and on human health in general are unpredictable and unique due to differences in practice of hospital oncology departments, in the number of patients, protection devices available, and the experience and safety procedures of medical staff. Health care workers who prepare or administer hazardous drugs or who work in areas where these drugs are used may be exposed to these agents in the air, on work surfaces, contaminated clothing, medical equipment, patient excreta, and other surfaces. These workers include specially pharmacists, pharmacy technicians, and nursing personnel. Exposures may occur through inhalation resulting from aerosolization of powder or liquid during reconstitution and spillage taking place while preparing or administering to patients, through Cytokinesis-block micronucleus test (CBMN) is extensively used in biomonitoring, since it determines several biomarkers of genotoxicity, such as micronuclei (MN), which are biomarkers of chromosomes breakage or loss, nucleoplasmic bridges (NPB), common biomarkers of chromosome rearrangement, poor repair and/or telomeres fusion, and nuclear buds (NBUD), biomarkers of elimination of amplified DNA.

Feature selection for clustering categorical data with an embedded modelling approach

Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

Clustering and selecting categorical features

In data clustering, the problem of selecting the subset of most relevant features from the data has been an active research topic. Feature selection for clustering is a challenging task due to the absence of class labels for guiding the search for relevant features. Most methods proposed for this goal are focused on numerical data. In this work, we propose an approach for clustering and selecting categorical features simultaneously. We assume that the data originate from a finite mixture of multinomial distributions and implement an integrated expectation-maximization (EM) algorithm that estimates all the parameters of the model and selects the subset of relevant features simultaneously. The results obtained on synthetic data illustrate the performance of the proposed approach. An application to real data, referred to official statistics, shows its usefulness.

Biodegradação enzimática de aminas aromáticas tóxicas

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Química e Biológica