Polycyclic aromatic hydrocarbons: levels and phase distributions in preschool microenvironment

This work aims to characterize levels and phase distribution of polycyclic aromatic hydrocarbons (PAHs) in indoor air of preschool environment and to assess the impact of outdoor PAH emissions to indoor environment. Gaseous and particulate (PM1 and PM2.5) PAHs (16 USEPA priority pollutants, plus dibenzo[a,l]pyrene, and benzo[j]fluoranthene) were concurrently sampled indoors and outdoors in one urban preschool located in north of Portugal for 35 days. The total concentration of 18 PAHs (ΣPAHs) in indoor air ranged from 19.5 to 82.0 ng/m3; gaseous compounds (range of 14.1–66.1 ng/m3) accounted for 85% ΣPAHs. Particulate PAHs (range 0.7–15.9 ng/m3) were predominantly associated with PM1 (76% particulate ΣPAHs) with 5-ring PAHs being the most abundant. Mean indoor/outdoor ratios (I/O) of individual PAHs indicated that outdoor emissions significantly contributed to PAH indoors; emissions from motor vehicles and fuel burning were the major sources.

Potential Therapeutic Effects of Physical Exercise for Bipolar Disorder

Cognitive deficits are observed in a variety of domains in patients with bipolar disorder (BD). These deficits are attributed to neurobiological, functional and structural brain factors, particularly in prefrontal cortex. Furthermore, cortical alterations in each phase (mania/hypomania, euthymia and depression) are also present. A growing basis of evidence supports aerobic exercise as an alternative treatment method for BD symptoms. Its benefits for physical health in healthy subjects and some psychiatric disorders are fairly established; however evidence directly addressed to BD is scant. Lack of methodological consistency, mainly related to exercise, makes it difficult accuracy and extrapolation of the results. Nevertheless, mechanisms related to BD physiopathology, such as hormonal and neurotransmitters alterations and mainly related to brain-derived neurotrophic factors (BDNF) can be explored. BDNF, specially, have a large influence on brain ability and its gene expression is highly responsive to aerobic exercise. Moreover, aerobic exercise trough BDNF may induce chronic stress suppression, commonly observed in patients with BD, and reduce deleterious effects caused by allostatic loads. Therefore, it is prudent to propose that aerobic exercise plays an important role in BD physiopathological mechanisms and it is a new way for the treatment for this and others psychiatric disorders.

Tuning metadata for better movie content-based recommendation systems

The increasing number of television channels, on-demand services and online content, is expected to contribute to a better quality of experience for a costumer of such a service. However, the lack of efficient methods for finding the right content, adapted to personal interests, may lead to a progressive loss of clients. In such a scenario, recommendation systems are seen as a tool that can fill this gap and contribute to the loyalty of users. Multimedia content, namely films and television programmes are usually described using a set of metadata elements that include the title, a genre, the date of production, and the list of directors and actors. This paper provides a deep study on how the use of different metadata elements can contribute to increase the quality of the recommendations suggested. The analysis is conducted using Netflix and Movielens datasets and aspects such as the granularity of the descriptions, the accuracy metric used and the sparsity of the data are taken into account. Comparisons with collaborative approaches are also presented.

Reliability of Two Methods for Identifying the Postural Phase of Gait Initiation in Healthy and Post-stroke Subjects

This study aims to compare two methods of assessing the postural phase of gait initiation as to intrasession reliability, in healthy and post-stroke subjects. As a secondary aim, this study aims to analyse anticipatory postural adjustments during gait initiation based on the centre of pressure (CoP) displacements in post-stroke participants. The CoP signal was acquired during gait initiation in fifteen post-stroke subjects and twenty-three healthy controls. Postural phase was identified through a baseline-based method and a maximal displacement based method. In both healthy and post-stroke participants higher intra-class correlation coefficient and lower coefficient of variation values were obtained with the baseline-based method when compared to the maximal displacement based method. Post-stroke participants presented decreased CoP displacement backward and toward the first swing limb compared to controls when the baseline-based method was used. With the maximal displacement based method, there were differences between groups only regarding backward CoP displacement. Postural phase duration in medial-lateral direction was also increased in post-stroke participants when using the maximal displacement based method. The findings obtained indicate that the baseline-based method is more reliable detecting the onset of gait initiation in both groups, while the maximal displacement based method presents greater sensitivity for post-stroke participants.

A Multi–Agent Brokerage Platform for Media Content Recommendation

Near real time media content personalisation is nowadays a major challenge involving media content sources, distributors and viewers. This paper describes an approach to seamless recommendation, negotiation and transaction of personalised media content. It adopts an integrated view of the problem by proposing, on the business-to-business (B2B) side, a brokerage platform to negotiate the media items on behalf of the media content distributors and sources, providing viewers, on the business-to-consumer (B2C) side, with a personalised electronic programme guide (EPG) containing the set of recommended items after negotiation. In this setup, when a viewer connects, the distributor looks up and invites sources to negotiate the contents of the viewer personal EPG. The proposed multi-agent brokerage platform is structured in four layers, modelling the registration, service agreement, partner lookup, invitation as well as item recommendation, negotiation and transaction stages of the B2B processes. The recommendation service is a rule-based switch hybrid filter, including six collaborative and two content-based filters. The rule-based system selects, at runtime, the filter(s) to apply as well as the final set of recommendations to present. The filter selection is based on the data available, ranging from the history of items watched to the ratings and/or tags assigned to the items by the viewer. Additionally, this module implements (i) a novel item stereotype to represent newly arrived items, (ii) a standard user stereotype for new users, (iii) a novel passive user tag cloud stereotype for socially passive users, and (iv) a new content-based filter named the collinearity and proximity similarity (CPS). At the end of the paper, we present off-line results and a case study describing how the recommendation service works. The proposed system provides, to our knowledge, an excellent holistic solution to the problem of recommending multimedia contents.

Ankle antagonist coactivation in the double-support phase of walking: Stroke vs. healthy subjects

Introduction: Lesions at ipsilateral systems related to postural control at ipsilesional side, may justify the lower performance of stroke subjects during walking. Purpose: To analyse bilateral ankle antagonist coactivation during double-support in stroke subjects. Methods: Sixteen (8 females; 8 males) subjects with a first isquemic stroke, and twenty two controls (12 females; 10 males) participated in this study. The double support phase was assessed through ground reaction forces and electromyography of ankle muscles was assessed in both limbs. Results: Ipsilesional limb presented statistical significant differences from control when assuming specific roles during double support, being the tibialis anterior and soleus pair the one in which this atypical behavior was more pronounced. Conclusion: The ipsilesional limb presents a dysfunctional behavior when a higher postural control activity was demanded.

High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.

Tecnologias Multimédia no Apoio ao Ensino da Assistência Pré-Hospitalar

Vivemos num mundo em constante mudança, onde a evolução tecnológica está cada vez mais presente no nosso quotidiano e as suas influências são inúmeras nas nossas vidas. Por outro lado, a vida humana é algo extremamente valioso e único pelo que a sociedade, também nessa área, tem procurado evoluir e dotar-se de novos meios e mecanismos de atuação, que possibilitem um socorro rápido e adequado em situações que possam em algum momento pôr em perigo a vida do ser humano. Pretendemos com o presente estudo, correlacionar estas duas vertentes, a do socorro á vítima para apoio á vida humana e a tecnologia no sentido de contribuir para uma formação mais distribuída mas ao mesmo tempo capaz de transmitir conhecimentos necessários á formação dos que socorrem. Para o efeito, planeamos o desenvolvimento de um Objeto de Aprendizagem (OA) denominado CiTAT (Curso Interativo de Tripulante de Ambulância de Transporte) que tem como objetivo acrescentar valor a todos os que são obrigados a frequentar o curso em regime presencial de Tripulante de Ambulância de Transporte (TAT). Após uma fase de análise do estado da arte relacionada com este tipo de formação, e após termos percebido como funciona e que tipos de recursos utilizam, analisámos temas relacionados com este tipo de formação como o “Sistema Integrado de Emergência Médica” o “Exame á Vítima”, o “Suporte Básico de Vida” e as “Emergências de Trauma”. Percebemos que a mudança de paradigma de formação das pessoas passou a ter novas formas de distribuir conhecimento em formato digital e que proporciona aos formandos um ensino distribuído em formatos de e-learning ou de b-learning. Os Objetos de Aprendizagem (OA) parecem assumir um relevo especial no ensino da área da saúde, abordando áreas temáticas e proporcionando aos seus utilizadores mecanismos de autoavaliação após a visualização dos conteúdos pedagógicos. Após o desenho do modelo concetual do CiTAT, avançamos para a produção de recursos necessários para a sua integração no OA. Após uma fase de testes e ajustes, avançamos para a sua avaliação final por parte dos utilizadores e preparamos um questionário para aferir o potencial de utilização deste tipo de soluções no ensino de TAT, atendendo ao facto de ser uma formação obrigatória e cuja recertificação é feita de três em três anos. O passo final foi a sua distribuição ao nível global, sendo o CiTAT catalogado com metadados e colocado no repositório MERLOT.

A framework for real time MMO game content generation

Com o aumento de plataformas móveis disponíveis no mercado e com o constante incremento na sua capacidade computacional, a possibilidade de executar aplicações e em especial jogos com elevados requisitos de desempenho aumentou consideravelmente. O mercado dos videojogos tem assim um cada vez maior número de potenciais clientes. Em especial, o mercado de jogos massive multiplayer online (MMO) tem-se tornado muito atractivo para as empresas de desenvolvimento de jogos. Estes jogos suportam uma elevada quantidade de jogadores em simultâneo que podem estar a executar o jogo em diferentes plataformas e distribuídos por um "mundo" de jogo extenso. Para incentivar a exploração desse "mundo", distribuem-se de forma inteligente pontos de interesse que podem ser explorados pelo jogador. Esta abordagem leva a um esforço substancial no planeamento e construção desses mundos, gastando tempo e recursos durante a fase de desenvolvimento. Isto representa um problema para as empresas de desenvolvimento de jogos, e em alguns casos, e impraticável suportar tais custos para equipas indie. Nesta tese e apresentada uma abordagem para a criação de mundos para jogos MMO. Estudam-se vários jogos MMO que são casos de sucesso de modo a identificar propriedades comuns nos seus mundos. O objectivo e criar uma framework flexível capaz de gerar mundos com estruturas que respeitam conjuntos de regras definidas por game designers. Para que seja possível usar a abordagem aqui apresentada em v arias aplicações diferentes, foram desenvolvidos dois módulos principais. O primeiro, chamado rule-based-map-generator, contem a lógica e operações necessárias para a criação de mundos. O segundo, chamado blocker, e um wrapper à volta do módulo rule-based-map-generator que gere as comunicações entre servidor e clientes. De uma forma resumida, o objectivo geral e disponibilizar uma framework para facilitar a geração de mundos para jogos MMO, o que normalmente e um processo bastante demorado e aumenta significativamente o custo de produção, através de uma abordagem semi-automática combinando os benefícios de procedural content generation (PCG) com conteúdo gráfico gerado manualmente.