Factores psicossociais preditivos de ajustamento à vida de pessoas com doenças crónicas

Doenças crónicas são de longa duração, de progressão lenta e induzem alterações na vida das pessoas, que são confrontadas com um conjunto de fatores que exercem um impacto negativo na sua qualidade de vida (QdV). A QdV é um conceito envolvendo componentes essenciais da qualidade humana: físicas, psicológicas, sociais, culturais e espirituais. Após o diagnóstico e com a doença estabilizada, os doentes procuram novas formas de lidar com esta. Este estudo teve como objetivo identificar fatores psicossociais preditivos (otimismo, afeto positivo e negativo, adesão aos tratamentos, suporte social e espiritualidade) da QdV (bem-estar geral, saúde física, saúde mental) e bem-estar subjetivo (BES) em pessoas com doenças crónicas. Amostra constituída por 774 indivíduos [30% diabetes, 27,1% cancro, 17,2% diabetes, 12% epilepsia, 11,5% esclerose múltipla e 2,2% miastenia, 70,5% do sexo feminino, idade M(DP)=42,9(11,6), educação M(DP)=9,6(4,7), anos diagnóstico M(DP)=12,8(9,7), classificação da doença M(DP)=6,6 (2,8)], recrutados nos hospitais centrais portugueses. Aplicando Modelos de Equações Estruturais e ajustando para variáveis sociodemográficas e clínicas, verificou-se que, pessoas mais otimistas, mais ativas e com uma melhor adesão aos tratamentos apresentam um melhor bem-estar geral, uma melhor saúde mental e um melhor bem-estar subjetivo; uma melhor adesão aos tratamentos contribui para uma melhor saúde física; melhor suporte social reflete-se numa melhor saúde mental; pessoas com mais espiritualidade apresentam uma melhor saúde física e uma melhor saúde mental. Estas conclusões contribuem para a definição de uma terapia que pode ajudar a uma melhor adaptação dos protocolos de tratamento para atender às necessidades dos doentes.

Práticas de literacia e avaliação da competência da escrita

O desfasamento entre a escola e os diferentes contextos sociais em que se insere, a dificuldade em dar resposta às solicitações e desafios que as suas comunidades lhe colocam, a deficiente preparação de muitos dos alunos para um uso competente e crítico da linguagem oral e escrita, constituem três críticas sérias ao papel atual da escola. O projeto que estamos a dinamizar com uma turma do ensino secundário procura contrariar este rumo da educação, demonstrando que é possível construir e valorizar as competências de literacia que não se circunscrevem à própria vida escolar, através de atividades de aprendizagem efetiva da escrita, numa relação interdisciplinar com outras áreas de conhecimento. Ele surge nos antípodas do ensino tradicional, onde a produção escrita é imposta aos alunos, tendo quase sempre o professor como único destinatário, valorizando-se aspetos de natureza formal e superficial em detrimento de outros que são fundamentais em termos de eficácia discursiva, fazendo dela depender, quase exclusivamente, a avaliação do aluno, muitas vezes assente numa mera reprodução de conhecimento.Assim, e com recurso à metodologia do trabalho de projeto, concebemos um roteiro paisagístico, ainda em fase de realização, acerca de uma quinta de D. Antónia (Ferreirinha), destinado aos seus turistas, que tem obrigado a uma participação no quadro mais alargado da escola enquanto comunidade e nas comunidades em que os seus membros se inserem, fazendo com que os alunos interajam com os contextos culturais, históricos, económicos, sociais e institucionais onde atuam, estudam e vivem: o Douro. Nesta comunicação, procuramos divulgar estas práticas e discutir a sua viabilidade, evidenciando o modo como os alunos constroem o seu saber sobre a língua e de que modo a avaliação é um processo indispensável quer nas diferentes etapas de elaboração de um projeto, quer no domínio da competência de escrita.

Dependent component analysis: a hyperspectral unmixing algorithm

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

Vertex component analysis: a fast algorithm to extract endmembers spectra from hyperspectral data

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

Vertex component analysis: a fast algorithm to unmix hyperspectral data

Given a set of mixed spectral (multispectral or hyperspectral) vectors, linear spectral mixture analysis, or linear unmixing, aims at estimating the number of reference substances, also called endmembers, their spectral signatures, and their abundance fractions. This paper presents a new method for unsupervised endmember extraction from hyperspectral data, termed vertex component analysis (VCA). The algorithm exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. In a series of experiments using simulated and real data, the VCA algorithm competes with state-of-the-art methods, with a computational complexity between one and two orders of magnitude lower than the best available method.

Comparison of the pencil beam convolution algorithm and the analytical anisotropic algorithm in breast tumors

The calculation of the dose is one of the key steps in radiotherapy planning1-5. This calculation should be as accurate as possible, and over the years it became feasible through the implementation of new algorithms to calculate the dose on the treatment planning systems applied in radiotherapy. When a breast tumour is irradiated, it is fundamental a precise dose distribution to ensure the planning target volume (PTV) coverage and prevent skin complications. Some investigations, using breast cases, showed that the pencil beam convolution algorithm (PBC) overestimates the dose in the PTV and in the proximal region of the ipsilateral lung. However, underestimates the dose in the distal region of the ipsilateral lung, when compared with analytical anisotropic algorithm (AAA). With this study we aim to compare the performance in breast tumors of the PBC and AAA algorithms.

A SON Enhanced Algorithm for Observed Time Differences Based Geolocation in Real 3G Networks

Conferência - 16th International Symposium on Wireless Personal Multimedia Communications (WPMC)- Jun 24-27, 2013

Detecção de sectores cruzados e optimização de cobertura em redes LTE

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Implementação em hardware reconfigurável de método de separação de dados hiperespetrais

Relatório do Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Comparação entre o pencil beam convolution algorithm e o analytical anisotropic algorithm em tumores de mama

Objectivo do estudo: comparar o desempenho dos algoritmos Pencil Beam Convolution (PBC) e do Analytical Anisotropic Algorithm (AAA) no planeamento do tratamento de tumores de mama com radioterapia conformacional a 3D.

Psychological well-being and perception of disease severity in people with multiple sclerosis, who underwent a program of self-regulation to promote physical activity

Rehabilitation is very important for in the results of treatment in individuals with multiple sclerosis. Rehabilitation processes occur through gradual changes. These changes integrate intrinsic and extrinsic mechanisms of the individual, promoting adaptations to the needs and activities of daily living according to individual goals. Recommendations for exercise in multiple sclerosis: these recommendations apply only to patients with EDSS less than 7; moderate intensity aerobic exercise for a total of 20 to 30 minutes, twice or three times for week; the resistance training with low or moderate intensity is well tolerated by patients with MS; associated with these exercises were recommended flexibility exercises of moderate intensity, as well as strengthening exercises. The aim of this study is to examine the implications of the program of self-regulation in the perception of illness and mental health (psychological well-being domain) in multiple sclerosis patients.

Importance of program physical activity in quality of life in multiple sclerosis patients, six months after the intervention

Background: Multiple Sclerosis (MS) is a chronic disease of the central nervous system that affects more often young adults in the prime of his career and personal development, with no cure and unknown causes. The most common signs and symptoms are fatigue, muscle weakness, changes in sensation, ataxia, changes in balance, gait difficulties, memory difficulties, cognitive impairment and difficulties in problem solving MS is a relatively common neurological disorder in which various impairments and disabilities impact strongly on function and daily life activities. Purpose: The aim of this study is to examine the implications of an Intervention Program of Physical Activity (IPPA) in quality of life in MS patients, six months after the intervention.

Evidence based for exercise program in physical therapy in patients with multiple sclerosis

Background: Multiple sclerosis is a disease of the central nervous system that affects more frequently young women. It is a progressive and unpredictable disease, resulting in some cases of disabilities and limitations to physical, psychological and social level. Purpose: To review the literature for evidence based of the effectiveness of physiotherapy intervention in multiple sclerosis.

Coding mode decision algorithm for binary descriptor coding

In visual sensor networks, local feature descriptors can be computed at the sensing nodes, which work collaboratively on the data obtained to make an efficient visual analysis. In fact, with a minimal amount of computational effort, the detection and extraction of local features, such as binary descriptors, can provide a reliable and compact image representation. In this paper, it is proposed to extract and code binary descriptors to meet the energy and bandwidth constraints at each sensing node. The major contribution is a binary descriptor coding technique that exploits the correlation using two different coding modes: Intra, which exploits the correlation between the elements that compose a descriptor; and Inter, which exploits the correlation between descriptors of the same image. The experimental results show bitrate savings up to 35% without any impact in the performance efficiency of the image retrieval task. © 2014 EURASIP.

Enabling Global Experiments With Interactive Reconfiguration And Steering By Multiple Users

In global scientific experiments with collaborative scenarios involving multinational teams there are big challenges related to data access, namely data movements are precluded to other regions or Clouds due to the constraints on latency costs, data privacy and data ownership. Furthermore, each site is processing local data sets using specialized algorithms and producing intermediate results that are helpful as inputs to applications running on remote sites. This paper shows how to model such collaborative scenarios as a scientific workflow implemented with AWARD (Autonomic Workflow Activities Reconfigurable and Dynamic), a decentralized framework offering a feasible solution to run the workflow activities on distributed data centers in different regions without the need of large data movements. The AWARD workflow activities are independently monitored and dynamically reconfigured and steering by different users, namely by hot-swapping the algorithms to enhance the computation results or by changing the workflow structure to support feedback dependencies where an activity receives feedback output from a successor activity. A real implementation of one practical scenario and its execution on multiple data centers of the Amazon Cloud is presented including experimental results with steering by multiple users.