Quality in Hospital Administrative Databases

The clinical content of administrative databases includes, among others, patient demographic characteristics, and codes for diagnoses and procedures. The data in these databases is standardized, clearly defined, readily available, less expensive than collected by other means, and normally covers hospitalizations in entire geographic areas. Although with some limitations, this data is often used to evaluate the quality of healthcare. Under these circumstances, the quality of the data, for instance, errors, or it completeness, is of central importance and should never be ignored. Both the minimization of data quality problems and a deep knowledge about this data (e.g., how to select a patient group) are important for users in order to trust and to correctly interpret results. In this paper we present, discuss and give some recommendations for some problems found in these administrative databases. We also present a simple tool that can be used to screen the quality of data through the use of domain specific data quality indicators. These indicators can significantly contribute to better data, to give steps towards a continuous increase of data quality and, certainly, to better informed decision-making.

Adaptive learning in agents behaviour: A framework for electricity markets simulation

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

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.

Modelo de avaliação de risco de crédito - rating - uma abordagem

Dissertação de Mestrado apresentada ao Instituto Superior de Contabilidade e Administração do Porto para a obtenção do Grau de Mestre em Auditoria, sob a orientação de Mestre Adalmiro Álvaro Malheiro de Castro Andrade Pereira

CMOS indoor light energy harvesting system for wireless sensing applications

This book discusses in detail the CMOS implementation of energy harvesting. The authors describe an integrated, indoor light energy harvesting system, based on a controller circuit that dynamically and automatically adjusts its operation to meet the actual light circumstances of the environment where the system is placed. The system is intended to power a sensor node, enabling an autonomous wireless sensor network (WSN). Although designed to cope with indoor light levels, the system is also able to work with higher levels, making it an all-round light energy harvesting system. The discussion includes experimental data obtained from an integrated manufactured prototype, which in conjunction with a photovoltaic (PV) cell, serves as a proof of concept of the desired energy harvesting system. © 2016 Springer International Publishing. All rights are reserved.

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.

Studies on human anti-rabies immunization in Brazil: I - Evaluation of the 3 + 1 pre-exposure vaccination schedule under field conditions

The currently used pre-exposure anti-rabies immunization schedule in Brazil is the one called 3+1, employing suckling mouse brain vaccine (3 doses on alternate days and the last one on day 30). Although satisfactory results were obtained in well controlled experimental groups using this immunization schedule, in our routine practice, VNA levels lower than 0.5 IU/ml are frequently found. We studied the pre-exposure 3+1 schedule under field conditions in different cities on the State of São Paulo, Brazil, under variable and sometimes adverse circumstances, such as the use of different batches of vaccine with different titers, delivered, stored and administered under local conditions. Fifty out of 256 serum samples (19.5%) showed VNA titers lower than 0.5 IU/ml, but they were not distributed homogeneously among the localities studied. While in some cities the results were completely satisfactory, in others almost 40% did not attain the minimum VNA titer required. The results presented here, considered separately, question our currently used procedures for human pre-exposure anti-rabies immunization. The reasons determining this situation are discussed.

Biomarkers in Solea Senegalensis Kaup, 1858 exposed to contaminated estuarine sediments: a multi-level approach

Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia for the degree of Doctor of Philosophy in Environmental Sciences

Cerebrospinal fluid profiles in acquired immunodeficiency syndrome with and without neurocryptococcosis

Cryptococcosis is one of the most common fungal infections of the central nervous system (CNS) in AIDS patients and meningoencephalitis or meningitis is a frequently observed manifestation. However, systematic studies of cerebrospinal fluid (CSF) composition from AIDS patients with CNS cryptococcosis have been few. CSF samples from 114 HIV seropositive patients whose clinical complaint suggested CNS involvement, were analyzed; 32 samples from patients diagnosed as having neurocryptococcosis (Group 1) and 82 samples from patients with no identified neurological disfunction (Group 2). Based on cytological and biochemical results, two distinct profiles were observed: Normal (Group 1 = 31%, Group 2 = 39%); Abnormal (Group 1 = 69%, Group 2 = 61%). Lymphocytes were the most frequent cells in both groups. Our CSF cytological and biochemical findings showed that in AIDS patients liquoric abnormalities are quite frequent, non-specific and difficult to interpret. In these circumstances a systematic search to identify the etiologic agent using microbiological and/or immunological assays must be routinely performed

IgM and IgA Antibody Responses in 12 Cases of Human Acquired Toxoplasmosis

The persistence, in some subjects, of specific IgM antibodies to Toxoplasma gondii for several months after the acute phase of infection has complicated the interpretation of serological test results for toxoplasmosis. Several reports have emphasized the value of the detection of Toxoplasma-specific IgA antibodies for the diagnosis of acute toxoplasmosis. In this article, we report the follow-up profiles of Toxoplasma-specific IgM and IgA antibodies in serum samples obtained from 12 patients at various intervals after the onset of the clinical manifestations of infection. IgM antibodies were detected by the indirect immunofluorescence (IIF) test, antibody capture enzyme-linked immunosorbent assay (cELISA) and enzyme-mediated chemilluminescent technique (CmL). IgA antibodies were quantified by the direct ELISA (dELISA) and cELISA procedures. As defined by the manufacturer of the cELISA test for IgA used, most patients with acute toxoplasmosis have antibody levels > 40 arbritary units per ml (AU/ml). At values > 40 AU/ml, the cELISA for IgA detected significant antibody levels for a shorter time than the other techniques used for IgM and IgA detection. However, IgA levels £ 40 AU/ml do not exclude the possibility of acute toxoplasmosis since such levels can be reached very soon after infection with T. gondii. The results obtained in the present study show that the serological diagnosis of acute toxoplasmosis may not be such an easy task. Our data suggest that use of the IgA-cELISA concomitantly with IgM antibody screening could permit, in some circumstances, a more efficient diagnosis of acute acquired toxoplasmosis

Sistemas de emprego público no século XXI: que significado? Uma sistematização

O presente artigo intenta sistematizar as formas ou regimes do emprego público em países da União Europeia e da OCDE. A metodologia compreende a análise dos tradicionais sistemas de carreira (career-based system) e sistema de emprego (position-based system) no emprego público. Desenvolvem-se, ainda, breves reflexões nas mudanças operadas naqueles dois regimes que migraram para um terceiro modelo, vulgarmente designado por modelo híbrido de emprego público, mais flexível e mais correlativo às circunstâncias do século XXI.

Constructing the National Canon in Ireland and Macedonia: The Function of Folklore in the Plays The Countess Cathleen and The Land of Heart’s Desire by William Butler Yeats, and Proud Flesh and The Black Hole by Goran Stefanovski and Their Role in Strengthening National Identity

Erasmus Mundus Masters “Crossways in European Humanities” June 2011

Implementação de um sistema de gestão da qualidade na empresa Qualidade de Basto, E.M.

Dissertação de Mestrado em Gestão Integrada da Qualidade, Ambiente e Segurança

Planeamento estratégico para abertura e implementação de um ginásio desportivo

Projeto apresentado ao Instituto Superior de Contabilidade e Administração do Porto para a obtenção do Grau de Mestre em Gestão das Organizações, Ramo de Gestão de Empresas. Orientada pelo Professor Doutor Eduardo Manuel Lopes de Sá e Silva Coorientada pelo Mestre Adalmiro Álvaro Malheiro de Castro Andrade Pereira

A gestão de informação nos processos de recrutamento e seleção de candidatos nas empresas de trabalho temporário

Dissertação apresentada ao Instituto Superior de Contabilidade e Administração do Porto para a obtenção do Grau de Mestre em Gestão das Organizações, Ramo de Gestão de Empresas Orientada por Prof. Doutor Eduardo Manuel Lopes de Sá e Silva Coorientada pela Mestre Maria de Fátima Mendes Monteiro Esta dissertação não inclui as críticas e sugestões feitas pelo Júri.