Entre a morfologia e a sintaxe : a formação de nomes deverbais em -da em português europeu

O objetivo do texto é analisar a formação de nomes deverbais em da em PortuguêsEuropeu (PE) e explorar a ideia de que tal processo de formação está ligado aoparticípio dos verbos, devendo o sufi xo da ser analisado em duas componentes: -d,forma do particípio propriamente dito e expressão da categoria verbal Asp, e -a, ummorfema nominal em que o feminino está estreitamente ligado ao traço de evento

Broadband in the public interest

If the UK’s government-led superfast fibre networks are rolled out on schedule, the country should have the fastest broadband connection in Europe by 2015. But what does this mean for the regular consumer? LSE’s Maria Paula Brito argues that even with the right technology in place, mass adoption is not going to be instant

So Close and Yet So Far: A Novella in Two Parts

So Close and Yet So Far is a novella in two parts, which takes place during two distinct time periods in Cuban history. The first part involves a female protagonist, Gloria Menocal Quintana, who begins her journey toward a singing career during the late 1940s, a time of great excess when the American and Italian Mafias held control of the nightclubs and casinos in Havana. Themes of sexual exploitation of women in entertainment, machismo, political upheaval, and infertility are explored in this section. The second part follows Gloria’s second cousin, Pedro Olivares, a young man who escapes Cuba on a raft in the early 1990s and suffers from culture shock and PTSD after arriving in Miami. Pedro visits Gloria in New York City a few years later, and, despite their large age difference, they bond over their past struggles and shared love for the homeland they left behind. While technically not historical fiction, the use of historical events and real settings are included to provide context and, possibly, a sense of relatability to some readers

To be a Barbie - a feasible dream

Publicado em "Proceedings CIMODE 2012 : 1º Congresso Internacional de Moda e Design". ISBN 978-972-8692-72-8From friend to partner Barbie was winning a legion of fans, and there are many girls who idealize seem like a doll. The utopia of perfect body leads to questioning the immersion of technique in life, i.e., the junction of the bios with technè, the hybridity between the organic and the inorganic. The new technical possibilities provide a number of opportunities, and what was until then an aspiration, volition, is realized today in a right and a duty that is claimed. All differences are converted to deviations from the norm consisting of the slim body, perfect, a model to be imitated and desired. The body has achieved a status: the playfulness, beauty and happiness are transversal to the cult of youth as a fetish. Thus, body dissatisfaction assumes normative condition and can lead to body image disorders

Applying machine learning algorithms to medical knowledge

Dissertação de mestrado integrado em Engenharia InformáticaAchieving great and undeniable success in a great variety of industries and businesses has made the term Big Data very popular among the scientific community. Big Data (BD) refers to the ever fast-growing research area in Computer Science (CS) that comprises many work areas across the world. The healthcare sector is widely known to be highly proficient in the production of big quantities of data. It can go from health information, such as the patient’s blood pressure and cholesterol levels, to more private and sensitive data, such as the medical procedures history or the report of ongoing diseases. The application of sophisticated techniques enables a profound and rigorous analysis of data, something a human cannot do in real-time. However, a machine is capable of rapidly collect, group, storage and examine vast amounts of data and extract unknown and possi bly interesting knowledge from it. The algorithms used can discover hidden relationships between attributes that prove to be very useful for a corporation’s work. Buried structures within the produced data can also be detected by these techniques. Machine Learning (ML) methods can be adjusted and modelled to different input representations - this adaptability is one of the factors that contributes to its blooming prosperity. The main goal is to make predictions on data, by building utterly efficient models that can accurately take in the data and thus predict a certain outcome. This is especially important to the healthcare industry since it can considerably improve the lives of many patients. Everything from detecting a type of disease, predicting the chance of morbidity after a hospital stay, to aid in the decision making of treatment strategies are vital to patients as well as to clinicians. Any improvement over established methods that have been previously studied, tested and published are an asset that will improve the patient’s satisfaction about the healthcare performance in medical institutions. This can be achieved by refining those algorithms or implementing new approaches that will make better predictions on the given data. The main objective of this dissertation is to propose ML approaches having acknowledged and evaluated the existent methods used in clinical data. In order to fulfill this goal, an analysis of the state of the art of medical knowledge repositories and scientific papers published related to the selected keywords selected was performed. In this line of work, it is crucial to understand, compare and discuss the results obtained to those previously published. Thus, one of the goals is to suggest new ways of solving those problems and measuring them up against the existent ones.Obter um sucesso enorme e inegável numa grande variedade de indústrias e companhias, tomou o termo Big Data (BD) muito popular entre a comunidade científica. Big Data refere-se à área de investigação em Engenharia Informática que revela um crescimento rápido e está envolvida em várias áreas em todo o mundo. O setor da saúde é universalmente con-hecido por ser altamente frutífero na produção de grandes quantidades de dados. Podem variar desde dados de saúde, tais como, o valor da pressão sanguínea e nível de coles-terol do paciente, até dados mais confidenciais, como o histórico de cirurgias realizadas e doenças diagnosticadas. A aplicação de técnicas sofisticadas permite uma análise profunda e rigorosa dos dados -algo que um ser humano não consegue fazer em tempo real. No entanto, uma máquina não tem dificuldades em recolher, agrupar, armazenar e analisar rapidamente grandes quanti-dades de dados e extrair deles conhecimento que era desconhecido e, possivelmente, interessante. Os algoritmos usados podem ser usados para descobrir relações desconhecidas entre os vários atributos, que se podem revelar bastante úteis para o dia-a-dia de uma empresa. Estruturas e padrões escondidos nos dados podem ser também detetados através das mesmas técnicas. Os métodos de Machine Learning (ML) podem ser ajustados e modela-dos de forma a aceitar diferentes representações de dados de entrada - esta adaptabilidade é um dos fatores mais proeminentes que contribui para a sua prosperidade. O principal objetivo é fazer previsões sobre os dados, de modo a construir modelos totalmente eficientes que possam analisar os dados de forma precisa, e, assim, prever um determinado resultado. Isto é especialmente importante para o setor da saúde, uma vez que pode melhorar consideravelmente a vida de muitos pacientes. Tudo, desde a deteção de um certo tipo de doença, prever a probabilidade de morbilidade após um internamento até a auxiliar na tomada de decisão em relação a estratégias de tratamento, é vital para os pacientes, bem como para os médicos. Portanto, qualquer melhoria em relação a métodos já estabelecidos que foram previamente estudados, testados e publicados é uma mais-valia que melhorará a satisfação do paciente em relação à sua experiência com os serviços de saúde. Tal pode ser alcançado refinando esses algoritmos ou mesmo implementando novas abordagens que farão melhores previsões sobre os dados. O principal objetivo desta dissertação é propor abordagens de ML, fazendo um reconhecimento e avaliando os métodos existentes utilizados em dados médicos. Desta forma, foi posta em prática uma análise ao estado da arte de repositórios de conhecimento médico, bem como a artigos científicos relacionados com esses conjuntos de dados. Assim, é fundamental compreender, comparar e discutir os resultados obtidos com os publicados anteriormente. Portanto, um dos objetivos é sugerir novas formas de resolver os problemas, tecendo uma comparação com os existentes

Nosocomial infections related to medical devices

Trabalho Final de Mestrado Integrado, Ciências Farmacêuticas, Universidade de Lisboa, Faculdade de Farmácia, 2017Hospital acquired infections are the fourth leading cause of disease in industrialised countries and the use of medical devices represents one of the most important risk factors to predispose patients to these infections. A substantial amount of common devices, like catheters and endotracheal tubes are used in hospital environment, and the insertion of more specialized medical devices, like prostheses or pacemakers and cardioverter-defibrillators is performed regularly. Once these devices are inserted, colonized by microorganisms, and covered by a biofilm, the chance of an infection is massive. But despite the risks, their utilization and application has increased over the years, so it is important to understand what are the major causative pathogens, their infection mechanism and how to battle them. The aim of the present work is to review the current literature regarding the pathogenesis of device-associated nosocomial infections, and to identify strategies of management and prevention for these infections.As infeções nosocomiais são a quarta principal causa de doença nos países industrializados e a utilização de dispositivos médicos é um dos fatores de risco associados mais importantes. No ambiente hospitalar são utilizados uma quantidade substancial de dispositivos comuns, como cateteres e tubos endotraqueais, e a inserção de dispositivos médicos mais especializados, como próteses ou pacemakers e cardioversores desfibrilhadores, é realizada regularmente. Assim que esses dispositivos são inseridos, colonizados por microrganismos e cobertos por um biofilme, a probabilidade do desenvolvimento de uma infeção é enorme. Apesar dos riscos, a sua utilização e aplicação aumentaram ao longo dos anos, por isso é importante entender quais são os principais agentes patogénicos responsáveis, o seu mecanismo de infeção e como combate-los. O objetivo do presente trabalho é rever a literatura quanto à patogénese das infeções nosocomiais associadas aos dispositivos médicos e identificar estratégias de tratamento e prevenção para as mesmas

CBmeter- a new medical device for early screening of metabolic diseases

Type 2 diabetes mellitus (T2DM) is a highly prevalent disease worldwide which is asymptomatic in about 44% of patients being critical to search for new ways of early diagnosis. Recent studies have demonstrated that the etiology of this disease may be associated with alterations in the function of the carotid body (CB), a chemosensor organ located within the bifurcation of the carotid artery. In animal models of metabolic syndrome it was observed that the CBs are overactivated, underlying diseases such as obesity, hypertension and T2DM. This discovery provided a new paradigm in the neuroendocrinology field, suggesting that diagnostic function of the CBs has predictive value for the development of metabolic diseases. Despite this fact, it is not common in clinical practice to look at the CBs as organs associated with endocrine dysfunction and we believe this is probably due to the nonexistence of a user-friendly, portable medical device that diagnosis the function of the CBs.info:eu-repo/semantics/publishedVersio

Sentiment and behaviour annotation in a corpus of dialogue summaries

This paper proposes a scheme for sentiment annotation. We show how the task can be made tractable by focusing on one of the many aspects of sentiment: sentiment as it is recorded in behaviour reports of people and their interactions. Together with a number of measures for supporting the reliable application of the scheme, this allows us to obtain sufficient to good agreement scores (in terms of Krippendorf's alpha) on three key dimensions: polarity, evaluated party and type of clause. Evaluation of the scheme is carried out through the annotation of an existing corpus of dialogue summaries (in English and Portuguese) by nine annotators. Our contribution to the field is twofold: (i) a reliable multi-dimensional annotation scheme for sentiment in behaviour reports; and (ii) an annotated corpus that was used for testing the reliability of the scheme and which is made available to the research community