PINPIN a-Si: H based structures for X-ray image detection using the laser scanning technique

Conventional film based X-ray imaging systems are being replaced by their digital equivalents. Different approaches are being followed by considering direct or indirect conversion, with the later technique dominating. The typical, indirect conversion, X-ray panel detector uses a phosphor for X-ray conversion coupled to a large area array of amorphous silicon based optical sensors and a couple of switching thin film transistors (TFT). The pixel information can then be readout by switching the correspondent line and column transistors, routing the signal to an external amplifier. In this work we follow an alternative approach, where the electrical switching performed by the TFT is replaced by optical scanning using a low power laser beam and a sensing/switching PINPIN structure, thus resulting in a simpler device. The optically active device is a PINPIN array, sharing both front and back electrical contacts, deposited over a glass substrate. During X-ray exposure, each sensing side photodiode collects photons generated by the scintillator screen (560 nm), charging its internal capacitance. Subsequently a laser beam (445 nm) scans the switching diodes (back side) retrieving the stored charge in a sequential way, reconstructing the image. In this paper we present recent work on the optoelectronic characterization of the PINPIN structure to be incorporated in the X-ray image sensor. The results from the optoelectronic characterization of the device and the dependence on scanning beam parameters are presented and discussed. Preliminary results of line scans are also presented. (C) 2014 Elsevier B.V. All rights reserved.

Host cell adhesion to Schistosoma mansoni larvae in the peritoneal cavity of naive mice: histological and scanning electron microscopic studies

Cercariae of Schistosoma mansoni inoculated into the peritoneal cavity of naive mice induced host cell adhesion to their surface, but after 90 minutes the number of adherent cells sharply decreased. The cell detachment is progressive and simultaneous to the cercaria-schistosomule transformation. The histological study showed mainly neutrophils in close contact with the larvae. Mononuclear cells and some eosinophils were occasionally seen surrounding the adherent neutrophils. The scanning electron microscopy showed cells displaying twisted microvilli and several microplicae contacting or spreading over the larval surface, and larvae completely surrounded by clusters of cells. These results suggest that the neutrophils recognize molecules on the cercarial surface which induce their spreading

Interaction between neutrophils and Schistosoma mansoni larvae in vivo: a transmission electron-microscopic study

Schistosoma mansoni cercariae were inoculated into the peritoneal cavity of naive mice and recovered 30 minutes later. Ultrastructural studies showed that neutrophils adhere to the larval surface and participate in the removal of glycocalyx by phagocytosis. This finding suggests that the neutrophils can play a role on the cercaria-schistosomulum transformation process.

Advanced image processing techniques for detection and quantification of drusen

Dissertation presented to obtain the degree of Doctor of Philosophy in Electrical Engineering, speciality on Perceptional Systems, by the Universidade Nova de Lisboa, Faculty of Sciences and Technology

A toolbox for hyperspectral image analysis

This paper introduces a new toolbox for hyperspectral imagery, developed under the MATLAB environment. This toolbox provides easy access to different supervised and unsupervised classification methods. This new application is also versatile and fully dynamic since the user can embody their own methods, that can be reused and shared. This toolbox, while extends the potentiality of MATLAB environment, it also provides a user-friendly platform to assess the results of different methodologies. In this paper it is also presented, under the new application, a study of several different supervised and unsupervised classification methods on real hyperspectral data.

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.

The visual image in Epiphanic Short History

The visual image is a fundamental component of epiphany, stressing its immediacy and vividness, corresponding to the enargeia of the traditional ekphrasis and also playing with cultural and social meanings. Morris Beja in his seminal book Epiphany in the Modern Novel, draws our attention to the distinction made by Joyce between the epiphany originated in a common object, in a discourse or gesture and the one arising in “a memorable phase of the mind itself”. This type materializes in the “dream-epiphany” and in the epiphany based in memory. On the other hand, Robert Langbaum in his study of the epiphanic mode, suggests that the category of “visionary epiphany” could account for the modern effect of an internally glowing vision like Blake’s “The Tyger”, which projects the vitality of a real tyger. The short story, whose length renders it a fitting genre for the use of different types of epiphany, has dealt with the impact of the visual image in this technique, to convey different effects and different aesthetic aims. This paper will present some examples of this occurrence in short stories of authors in whose work epiphany is a fundamental concept and literary technique: Walter Pater, Joseph Conrad, K. Mansfield, Clarice Lispector. Pater’s “imaginary portraits” concentrate on “priviledged moments” of the lives of the characters depicting their impressions through pictorial language; Conrad tries to show “moments of awakening” that can be remembered by the eye; Mansfield suggests that epiphany, the “glimpse”, should replace plot as an internal ordering principle of her impressionist short-stories; in C. Lispector the visualization of some situations is so aggressive that it causes nausea and a radical revelation on the protagonist’s.

THE PERSISTENCE OF LEPTOSPIRAL AGGLUTININS TITERS IN HUMAN SERA DIAGNOSED BY THE MICROSCOPIC AGGLUTINATION TEST

The persistence of agglutinins detected by MAT has created some problems to the interpretation of the results. The aim of this study was to examine the data of serology from 70 patients with serologically confirmed diagnosis of leptospirosis by during 3-13 months after being affected with leptospires in order to elucidate the interpretation of the persistence of agglutinins detected by MAT. Sixty-one patients sera (87.14%) had titers equal or greater than 800. Of these, two individuals maintained titers of 800 thirteen months after the onset. This study showed that only one sample of sera with high titers is not reliable to determine the time at which infection occurred.

Automated image tagging through tag propagation

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial Para obtenção do grau de Mestre em Engenharia Informática

Une langue étragère, un ordinateur, une image: c'est simple comme bonjour!

Este artigo surgiu na sequência de um atelier “Une langue étrangère, un ordinateur, une image: c’est simple comme bonjour!”, desenvolvido no âmbito do XXI Congresso da Associação Portuguesa dos Professores de Francês, Images et imaginaires pour agir. Teve como propósito divulgar, experimentar e refletir sobre recursos digitais que podem dar um bom contributo ao processo de ensino e aprendizagem do Francês Língua Estrangeira (FLE). Evidencia-se o poder da imagem na construção do conhecimento, desafiando a criatividade e novos modos de ensinar a aprender. Verificou-se que os professores se interessaram pelas ferramentas digitais e evidenciaram a sua importância e a sua aplicabilidade nos contextos educativos. Neste sentido, o artigo divulga ferramentas informáticas focadas no desenvolvimento da oralidade/leitura/escrita do francês língua estrangeira, refere boas práticas de utilização em contexto de sala de aula, constituindo uma contribuição para a renovação da escola.

Identification of Cryptosporidium spp. oocysts in fecal smears stained with Heidenhain's iron hematoxylin

There is no paucity of methods for diagnosing Cryptosporidium spp. infection. The merits of immunoassays notwithstanding, microscopic identification of Cryptosporidium spp. oocysts in fecal samples remains an important diagnostic procedure. It owes the persistence of its use to such characteristics as dispensing with expensive equipment and kits, requiring only basic laboratory facilities, and having a low probability of false positive results when permanent slides are prepared, which can be re-examined in case of doubt. Cryptosporidium spp. oocysts can be readily identified in fecal smears prepared according to a regressive iron hematoxylin staining technique. The number of steps and their duration, as well as costs, were reduced to a minimum without loss of image quality and permanence of the preparations.

The role of cultural mega events In the enhancement of city’s image attributes

In a time of fierce competition between regions, an image serve as a basis to develop a strong sense of community, which fosters trust and cooperation that can be mobilized for regional growth. A positive image and reputation could be used in the promotional activities of the region benefiting all the stakeholders as a whole. Mega cultural events are frequently used to attract tourists and investments to a region, but also to enhance the city’s image. This study adopts a marketing/communication perspective of city’s image, and intends to explain how the image of the city is perceived by their residents. Specifically, we intend to compare the perceptions of residents that effectively participated in the Guimarães European Capital of Culture (ECOC) 2012 (engaged residents), and the residents that only assisted to the event (attendees). Several significant findings are reported and their implications for event managers and public policy administrators presented, along with the limitations of the study.

Quantification and viability analyses of Pseudokirchneriella subcapitata algal cells using image-based cytometry

This work aims to evaluate the feasibility of using image-based cytometry (IBC) in the analysis of algal cell quantification and viability, using Pseudokirchneriella subcapitata as a cell model. Cell concentration was determined by IBC to be in a linear range between 1 × 105 and 8 × 106 cells mL−1. Algal viability was defined on the basis that the intact membrane of viable cells excludes the SYTOX Green (SG) probe. The disruption of membrane integrity represents irreversible damage and consequently results in cell death. Using IBC, we were able to successfully discriminate between live (SG-negative cells) and dead algal cells (heat-treated at 65 °C for 60 min; SG-positive cells). The observed viability of algal populations containing different proportions of killed cells was well correlated (R 2 = 0.994) with the theoretical viability. The validation of the use of this technology was carried out by exposing algal cells of P. subcapitata to a copper stress test for 96 h. IBC allowed us to follow the evolution of cell concentration and the viability of copper-exposed algal populations. This technology overcomes several main drawbacks usually associated with microscopy counting, such as labour-intensive experiments, tedious work and lack of the representativeness of the cell counting. In conclusion, IBC allowed a fast and automated determination of the total number of algal cells and allowed us to analyse viability. This technology can provide a useful tool for a wide variety of fields that utilise microalgae, such as the aquatic toxicology and biotechnology fields.

Gesture based interface for image annotation

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Informática pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia