Early literacy development in Catalan: characteristics and instructional influence

Resumo: Este artigo analisa a relação entre o nível de consciência fonológica, conhecimento das letra e as estratégias utilizadas para ler e escrever, em crianças de cinco anos, ensinadas em catalão. Participaram 69 crianças de três classes diferentes. Cada um dos seus professores utilizava um método diferente de ensino: analítico, sintético ou analítico-sintético. As crianças foram avaliadas no início e no final do ano letivo em: Reconhecimento de letras, segmentação palavra oral, leitura de palavras, leitura de um texto curto e um ditado. Foram realizadas análises de granulação fina em nas respostas das crianças, para identificar estratégias e padrões específicos. A análise qualitativa indica que a capacidade de segmentar uma palavra em sílabas por via oral parece ser suficiente para as crianças começarem a ler de uma forma convencional. Além disso, a consciência fonológica e o conhecimento das letras são usados em formas relativamente diferentes, dependendo do tipo de texto a ser lido. As abordagens de ensino dos professores parecem ter uma influência nos resultados das crianças.

Development of TNBS-induced colitis: animal model to test new pharmacological approaches

IBD is a gastro-intestinal disorder marked with chronic inflammation of intestinal epithelium, damaging mucosal tissue and manifests into several intestinal and extra-intestinal symptoms. Currently used medical therapy is able to induce and maintain the patient in remission, however no modifies or reverses the underlying pathogenic mechanism. The research of other medical approaches is crucial to the treatment of IBD and, for this, it´s important to use animal models to mimic the characteristics of disease in real life. The aim of the study is to develop an animal model of TNBS-induced colitis to test new pharmacological approaches. TNBS was instilled intracolonic single dose as described by Morris et al. It was administered 2,5% TNBS in 50% ethanol through a catheter carefully inserted into the colon. Mice were kept in a Tredelenburg position to avoid reflux. On day 4 and 7, the animals were sacrificed by cervical dislocation. The induction was confirmed based on clinical symptoms/signs, ALP determination and histopathological analysis. At day 4, TNBS group presented a decreased body weight and an alteration of intestinal motility characterized by diarrhea, severe edema of the anus and moderate morbidity, while in the two control groups weren’t identified any alteration on the clinical symptoms/signs with an increase of the body weight. TNBS group presented the highest concentrations of ALP comparing with control groups. The histopathology analysis revealed severe necrosis of the mucosa with widespread necrosis of the intestinal glands. Severe hemorrhagic and purulent exsudates were observed in the submucosa, muscular and serosa. TNBS group presented clinical symptoms/signs and histopathological features compatible with a correct induction of UC. The peak of manifestations became maximal at day 4 after induction. This study allows concluding that it’s possible to develop a TNBS induced colitis 4 days after instillation.

Development and validation of a psychometric scale for assessing PA chest image quality: a pilot study

Purpose - To develop and validate a psychometric scale for assessing image quality perception for chest X-ray images. Methods - Bandura's theory was used to guide scale development. A review of the literature was undertaken to identify items/factors which could be used to evaluate image quality using a perceptual approach. A draft scale was then created (22 items) and presented to a focus group (student and qualified radiographers). Within the focus group the draft scale was discussed and modified. A series of seven postero-anterior chest images were generated using a phantom with a range of image qualities. Image quality perception was confirmed for the seven images using signal-to-noise ratio (SNR 17.2–36.5). Participants (student and qualified radiographers and radiology trainees) were then invited to independently score each of the seven images using the draft image quality perception scale. Cronbach alpha was used to test interval reliability. Results - Fifty three participants used the scale to grade image quality perception on each of the seven images. Aggregated mean scale score increased with increasing SNR from 42.1 to 87.7 (r = 0.98, P < 0.001). For each of the 22 individual scale items there was clear differentiation of low, mid and high quality images. A Cronbach alpha coefficient of >0.7 was obtained across each of the seven images. Conclusion - This study represents the first development of a chest image quality perception scale based on Bandura's theory. There was excellent correlation between the image quality perception scores derived using the scale and the SNR. Further research will involve a more detailed item and factor analysis.

Metodologia de projeto como estratégia de motivação e criatividade na disciplina de artes plásticas

Mestrado em Ensino de Educação Visual e Tecnológica no Ensino Básico

Research practice development for nuclear medicine technologists: an innovative experience

Introduction - European nuclear medicine technologist’s education is delivered by Higher Education Institutions and students obtain a grade of Bachelor of Sciences (BSc), during which they are initiated to research during their studies. Once BSc nuclear medicine technologists are in professional practice, they have very few opportunities to develop a real research experience and they rather become passive users than active contributors the growth of scientific knowledge in nuclear medicine. Aim - To describe and discuss an innovative educational and professional experience aimed in strengthen research knowledge, skills and competencies of former nuclear medicine technologists student in the context of an international mobility stay.

Accessibility and Local Development: Interaction between Cross-border Accessibility and Local Development in Portugal and Spain

One of de EU major concerns is cohesion and cross-border regional development. Usually cross-border regions are less dynamic, acting as bottlenecks mainly in peripheral territories. This paper is focused on the Portuguese-Spanish border using socio-economic and accessibility data. It considers Spatial Econometrics to produce statistical evidence on the relationship between accessibility and development at a local scale. A pilot study is conducted on North and Center region using variables such as population age, graduation characteristics, migrations, unemployment and daily accessibility to main towns in future this evaluation will be applied to the entire cross-border area between Portugal and Spain.

The effects of clinical support surfaces on pressure as a risk factor in the development of pressure ulcers, from a radiographical perspective: a narrative literature review

Purpose: Pressure ulcers are a high cost, high volume issue for health and medical care providers, having a detrimental effect on patients and relatives. Pressure ulcer prevention is widely covered in the literature, but little has been published regarding the risk to patients in the radiographical setting. This review of the current literature is to identify findings relevant to radiographical context. Methods: Literature searching was performed using Science Direct and Medline databases. The search was limited to articles published in the last ten years to remain current and excluded studies containing participants less than 17 years of age. In total 14 studies were acquired; three were excluded as they were not relevant. The remaining 11 studies were compared and reviewed. Discussion: Eight of the studies used ‘healthy’ participants and three used symptomatic participants. Nine studies explored interface pressure with a range of pressure mat technologies, two studies measured shear (MRI finite element modelling, and a non-invasive instrument), and one looked at blood flow and haemoglobin oxygenation. A range of surfaces were considered from trauma, nursing and surgical backgrounds for their ability to reduce pressure including standard mattresses, high specification mattresses, rigid and soft layer spine boards, various overlays (gel, air filled, foam). Conclusion: The current literature is not appropriate for the radiographic patient and cannot be extrapolated to a radiologic context. Sufficient evidence is presented in this review to support the need for further work specific to radiography in order to minimise the development of PU in at risk patients.

A stochastic programming approach for the development of offering strategies for a wind power producer

A stochastic programming approach is proposed in this paper for the development of offering strategies for a wind power producer. The optimization model is characterized by making the analysis of several scenarios and treating simultaneously two kinds of uncertainty: wind power and electricity market prices. The approach developed allows evaluating alternative production and offers strategies to submit to the electricity market with the ultimate goal of maximizing profits. An innovative comparative study is provided, where the imbalances are treated differently. Also, an application to two new realistic case studies is presented. Finally, conclusions are duly drawn.

Approaches to tuberculosis mucosal vaccine development using nanoparticles and microparticles: a review

Next-generation vaccines for tuberculosis should be designed to prevent the infection and to achieve sterile eradication of Mycobacterium tuberculosis. Mucosal vaccination is a needle-free vaccine strategy that provides protective immunity against pathogenic bacteria and viruses in both mucosal and systemic compartments, being a promising alternative to current tuberculosis vaccines. Micro and nanoparticles have shown great potential as delivery systems for mucosal vaccines. In this review, the immunological principles underlying mucosal vaccine development will be discussed, and the application of mucosal adjuvants and delivery systems to the enhancement of protective immune responses at mucosal surfaces will be reviewed, in particular those envisioned for oral and nasal routes of administration. An overview of the essential vaccine candidates for tuberculosis in clinical trials will be provided, with special emphasis on the potential different antigens and immunization regimens.

Development and validation of a psychometric scale for assessing PA chest image quality

Purpose - To develop and validate a psychometric scale for assessing image quality for chest radiographs.

Toroid inductor development for a SIC DC-DC converter up to 150kW, based on finite element method

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

Development of a high-throughput monitoring technique of bacteria photodynamic inactivation

Summary form only given. Bacterial infections and the fight against them have been one of the major concerns of mankind since the dawn of time. During the `golden years' of antibiotic discovery, during the 1940-90s, it was thought that the war against infectious diseases had been won. However currently, due to the drug resistance increase, associated with the inefficiency of discovering new antibiotic classes, infectious diseases are again a major public health concern. A potential alternative to antibiotic treatments may be the antimicrobial photodynamic inactivation (PDI) therapy. To date no indication of antimicrobial PDI resistance development has been reported. However the PDI protocol depends on the bacteria species [1], and in some cases on the bacteria strains, for instance Staphylococcus aureus [2]. Therefore the development of PDI monitoring techniques for diverse bacteria strains is critical in pursuing further understanding of such promising alternative therapy. The present works aims to evaluate Fourier-Transformed-Infra-Red (FT-IR) spectroscopy to monitor the PDI of two model bacteria, a gram-negative (Escherichia coli) and a gram-positive (S. aureus) bacteria. For that a high-throughput FTIR spectroscopic method was implemented as generally described in Scholz et al. [3], using short incubation periods and microliter quantities of the incubation mixture containing the bacteria and the PDI-drug model the known bactericidal tetracationic porphyrin 5,10,15,20-tetrakis (4-N, N, Ntrimethylammoniumphenyl)-porphyrin p-tosylate (TTAP4+). In both bacteria models it was possible to detect, by FTIR-spectroscopy, the drugs effect on the cellular composition either directly on the spectra or on score plots of principal component analysis. Furthermore the technique enabled to infer the effect of PDI on the major cellular biomolecules and metabolic status, for example the turn-over metabolism. In summary bacteria PDI was monitored in an economic, rapid (in minutes- , high-throughput (using microplates with 96 wells) and highly sensitive mode resourcing to FTIR spectroscopy, which could serve has a technological basis for the evaluation of antimicrobial PDI therapies efficiency.

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.