Autoeficácia percebida na eficácia docente : uma auscultação a professores do ensino básico

XII Congresso Internacional Galego-Português de Psicopedagogia, realizado nos dias 11, 12 e 13 de Setembro de 2013, na Universidade do Minho (Campus de Gualtar).

Escala de autoeficácia percebida na docência (ECAD) : adaptação e validação para Portugal

Comunicação apresentada no XII Congresso Internacional Galego-Português de Psicopedagogia, realizado nos dias 11, 12 e 13 de Setembro de 2013, na Universidade do Minho (Campus de Gualtar).

A Natividade Nunes da Silva : carpetes, colchas, tapetes e linhos de Belver : de manufatura a unidade de memória

Dissertação de Mestrado, Património, Museologia e Desenvolvimento, 12 de Novembro de 2015, Universidade dos Açores.

Accomodating students with disabilities in academic and institucional contexts

Sunflower Conference 2009 11-12 November, Ostrava Third annual internacional conference

The periodic table: contest and exhibition

The systemization and organization of ideas and concepts is an integral part of science. In chemistry, the organization of the periodic table of the chemical elements in the 1860s was one of the greatest scientific breakthroughs ever made and in fact during the 20th century it became a universally recognized scientific icon (1). The periodic table is the fundamental classificatory scheme of the elements and summarizes the realm of chemistry (2). Simply knowing the position of an element in the periodic table tells us about its properties and is usually enough to predict how the element will behave in a wide variety of different situations or reactions (1). Based on this potential mine of information, it is possible to make reliable predictions of the properties of the compounds that each element forms. Nowadays, the concept of the periodic table is starting to interact with other sciences and reports of periodic tables of amino acids (3), genetic codes (4), protein structures (5), and biology (6) can be found in the specialized literature. Symbiosis between science and art, for example, “The Periodic Table of The Elephants” (7), can also be seen. To appeal to a better understanding of the periodic table, the Instituto Superior de Engenharia do Instituto Politécnico do Porto and the Centro de Química da Universidade do Porto promoted a contest and exhibit with the goal of stimulating a wide and heterogeneous audience, ranging from young children and their parents to graduate students from several disciplines, to explore the nature of this icon. Imaginative educational activities such as contests (8–10), games (11, 12), and puzzles (13–15) provided a way to communicate with the general public with the goal of attracting students to science. This also constituted an interesting, informative, and entertaining alternative to non-interactive lectures. Simultaneously, artistic creativity was combined with scientific knowledge.

Baryogenesis through split higgsogenesis

We study the cosmological evolution of asymmetries in the two-Higgs doublet extension of the Standard Model, prior to the electroweak phase transition. If Higgs flavour-exchanging interactions are sufficiently slow, then a relative asymmetry among the Higgs doublets corresponds to an effectively conserved quantum number. Since the magnitude of the Higgs couplings depends on the choice of basis in the :Higgs doublet space, we attempt to formulate basis-independent out-of-equilibrium conditions. We show that an initial asymmetry between the fliggs scalars, which could be generated by GP violation in the :Higgs sector, will be transformed into a baryon asymmetry by the sphalerons, without the need of B - L violation. This novel mechanism of baryogenesis through (split) Higgsogenesis is exemplified with simple scenarios based on the out-of-equilibrium decay of heavy singlet scalar fields into the illiggs doublets.

Os processos de criação artística enquanto fatores potenciadores e inibidores da inter e transdisciplinaridade

A criação artística há muito que evoluí a par com desenvolvimento tecnológico. As novas tecnologias e as novas ferramentas que lhes estão associadas têm possibilitado não só novos meios de expressão, como também contribuído para uma alteração do próprio processo criativo. Desde a câmara obscura utilizada por Canaletto às imagens algorítmicas de George Legrady, muitos são os exemplos da influência das novas tecnologias na expressão e evolução da criação artística. Porém, a esta evolução estão também associadas transformações nos processos de trabalho, e no modo de colaboração entre as várias áreas de saber e suas diferentes especialidades. Os processos condicionam os resultados e no caso concreto do campo artístico representam importantes fatores potenciadores ou condicionadores da interdisciplinaridade e da transdisciplinaridade. Se, por um lado, as tecnologias digitais potenciam uma maior colaboração entre profissionais, por outro poderão ser responsáveis por uma maior fragmentação e hiperespecialização das diferentes fases do processo criativo. As plataformas de convergência, através da standartização de linguagens e ferramentas, induzem a criação artística para uma uniformização dos processos e para uma consequente uniformização dos resultados. A presente comunicação propõe uma reflexão, através da análise de diferentes estudos de caso, sobre a influência dos processos criativos e diferentes metodologias de projeto das artes audiovisuais na inter e transdisciplinaridade.

Avaliação da conduta conservadora na lesão intraepitelial cervical de alto grau

OBJETIVO: Analisar a associação entre a conduta conservadora em lesão intraepitelial cervical de alto grau com o índice de recidiva da neoplasia e faixa etária. MÉTODOS: Estudo transversal e retrospectivo realizado com 509 mulheres (15-76 anos) atendidas no período de 1996 a 2006, com colpocitologia oncótica alterada, em um serviço público de referência em Maringá, PR. Os dados foram coletados dos prontuários médicos e estudadas as variáveis diagnóstico definitivo, tipos de tratamento, ocorrência da lesão e recidivas, analisados por meio de testes de associação de qui-quadrado de Pearson e teste exato de Fisher. RESULTADOS: A lesão intraepitelial cervical de alto grau ocorreu em 168 casos; destes, 31 mulheres foram submetidas à amputação cônica, 104 a cirurgias de alta frequência, nove histerectomizadas e 24 receberam conduta conservadora. Dentre as mulheres com lesão de alto grau e tratadas de forma conservadora, oito (33,3%) recidivaram, enquanto dentre as submetidas à conduta não conservadora dez (6,9%) recidivaram, sendo essa diferença estatisticamente significante (p = 0,0009), RP = 4,8 (IC95% 2,11;10,93). Para aquelas que fizeram o seguimento clínico-citológico, três (30,0%) e, dentre as cauterizadas, cinco (35,7%) recidivaram no prazo de três anos, sem diferença significante (p = 0,5611). A recidiva abaixo e acima de 30 anos ocorreu, respectivamente, em sete (13,8%) e 11 (12,2%) mulheres (p = 0,9955). CONCLUSÕES: A idade da mulher não influencia o prognóstico de recidiva. O tratamento conservador deve ser indicado como conduta de exceção, dada a alta taxa de recidiva, e o seguimento deve ser rigoroso, com acompanhamento citológico e colposcópico de até três anos, período em que ocorre a maioria das recidivas.

Tunnig optical A-Sic/A-Si active filters by UV bias light in the visible and infrared spectral ranges

Visible range to telecom band spectral translation is accomplished using an amorphous SiC pi'n/pin wavelength selector under appropriate front and back optical light bias. Results show that background intensity works as selectors in the infrared region, shifting the sensor sensitivity. Low intensities select the near-infrared range while high intensities select the visible part according to its wavelength. Here, the optical gain is very high in the infrared/red range, decreases in the green range, stays close to one in the blue region and strongly decreases in the near-UV range. The transfer characteristics effects due to changes in steady state light intensity and wavelength backgrounds are presented. The relationship between the optical inputs and the output signal is established. A capacitive optoelectronic model is presented and tested using the experimental results. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Viability of the use of an A-SiC:H multiplayer device in a domestic VLC application

In this paper the viability of an integrated wavelength optical filter and photodetector for visible light communication (VLC) is discussed. The proposed application uses indoor warm light lamps lighting accomplished by ultra-bright light-emitting diodes (LEDs) pulsed at frequencies higher than the ones perceived by the human eye. The system was analyzed at two different wavelengths in the visible spectrum (430 nm and 626 nm) with variable optical intensities. The signals were transmitted into free space and measured using a multilayered photodetector based on a-SiC:H/a-Si:H. The detector works as an optical filter with controlled wavelength sensitivity through the use of optical bias. The output photocurrent was measured for different optical intensities of the transmitted optical signal and the extent of each signal was tested. The influence of environmental fluorescent lighting was also analysed in order to test the strength of the system. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Viability of the use of thin-film A-SiC:H photodiodes for protein identification

In this paper, we present a multilayer device based on a-Si:H/a-SiC:H that operates as photodetector and optical filter. The use of such device in protein detection applications is relevant in Fluorescence Resonance Energy Transfer (FRET) measurements. This method demands the detection of fluorescent signals located at specific wavelengths bands in the visible part of the electromagnetic spectrum. The device operates in the visible range with a selective sensitivity dependent on electrical and optical bias. Several nanosensors were tested with a commercial spectrophotometer to assess the performance of FRET signals using glucose solutions of different concentrations. The proposed device was used to demonstrate the possibility of FRET signals detection, using visible signals of similar wavelength and intensity. The device sensitivity was tuned to enhance the wavelength band of interest using steady state optical bias at 400 nm. Results show the ability of the device to detect signals in this range. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. 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. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

A comparative study of severe scorpion envenomation in children caused by Tityus bahiensis and Tityus serrulatus

From January 1984 to May 1994, 17 of 239 children under 15 years old stung by Tityus serrulatus (15.1%) or Tityus bahiensis (84.9%) presented severe envenoming. Of these 17 patients (1-11 years old; median=2 yr) 14 were stung by T.serrulatus and three by T.bahiensis. All of them received scorpion antivenom i.v. at times ranging from 45 min. to 5 h after the accident (median=2h). On admission, the main clinical manifestations and laboratory and electrocardiographic changes were: vomiting (17), diaphoresis (15), tachycardia (14), prostration (10), tachypnea (8), arterial hypertension (7), arterial hypotension (5), tremors (5), hypothermia (4), hyperglycemia (17), leukocytosis (16/16), hypokalemia (13/17), increased CK-MB enzyme activity (>6% of the total CK, 11/12), hyperamylasemia (11/14), sinusal tachycardia (16/17) and a myocardial infarction-like pattern (11/17). Six patients stung by T.serrulatus had depressed left ventricular systolic function assessed by means of echocardiography. Of these, five presented pulmonary edema and four had shock. A child aged two-years old presented severe respiratory failure and died 65 h after being stung by T.serrulatus. Severe envenomations caused by T.serrulatus were 26.2 times more frequent than those caused by T.bahiensis (p<0.001).

Every normal logic program has a 2-valued semantics: theory, extensions, applications, implementations

Trabalho apresentado no âmbito do Doutoramento em Informática, como requisito parcial para obtenção do grau de Doutor em Informática