Da proficuidade da migração das palavras na literatura ao seu desvirtuamento na imprensa

A importância da migração das palavras para diferentes contextos de uso, propiciados pela sua geografia peculiar, no âmbito da literatura coeva, terreno privilegiado para a sua ocorrência. Contributo da concretização deste movimento para a ampliação da pluralidade das significações e diversificação do leque de utilizações das palavras. Enfocadas a partir de cinco ângulos de abordagem prioritários: os portugueses, a partida, o amor, a mulher e o homem. Desaproveitamento e desvirtuamento, na imprensa, das potencialidades proporcionadas pela ductilidade da linguagem. The importance of word migration into other context, made possible by its peculiar geography, in coeval literature, the propitious site for it to happen. Importance of this movement concreteness to amplify the signification variety and diversification of word use situations. Watched from five priority approach angles: the Portuguese, the departure, love, woman and man. The waste and tainting, in press, of all potentialities made possible by language malleability

Using mobile device detection approaches to augment the accuracy of web delivery content

Recent studies of mobile Web trends show a continuous explosion of mobile-friendly content. However, the increasing number and heterogeneity of mobile devices poses several challenges for Web programmers who want to automatically get the delivery context and adapt the content to mobile devices. In this process, the devices detection phase assumes an important role where an inaccurate detection could result in a poor mobile experience for the enduser. In this paper we compare the most promising approaches for mobile device detection. Based on this study, we present an architecture for a system to detect and deliver uniform m-Learning content to students in a Higher School. We focus mainly on the devices capabilities repository manageable and accessible through an API. We detail the structure of the capabilities XML Schema that formalizes the data within the devices capabilities XML repository and the REST Web Service API for selecting the correspondent devices capabilities data according to a specific request. Finally, we validate our approach by presenting the access and usage statistics of the mobile web interface of the proposed system such as hits and new visitors, mobile platforms, average time on site and rejection rate

Are There Non-linear Relationships between Ownership Structure and Operational Performance? Empirical Evidence from Portuguese SMEs Using Dynamic Panel Data

This paper analyzes the causal relationship between the ownership concentration, insider ownership and operational performance using a sample of 4.163 Portuguese SMEs and panel data models. The main results show an endogenous and dynamic relationship between those variables. The quadratic specification established between ownership concentration and operational profitability suggests that for low levels of control rights the expropriation hypothesis prevails and for high levels the supervision hypothesis prevails. It was also possible to validate the effect of entrenchment and convergence of interests in the relationship established between the insider ownership and performance

Banking Relationships, Managerial Ownership and Operational Performance: A Simultaneous Equations Approach in the Context of SMEs

This paper provides new evidence for the relationship between the nature of banking relationships, managerial ownership and operational performance in supporting reciprocal effects between these variables in the context of small and medium enterprises (SMEs). A simultaneous equations model was applied to a sample of 4,163 Portuguese SMEs and to cross-section data. Evidence was found that these attributes provide simultaneous relations among themselves. In particular, on the one hand, our results support a negative effect of the number of banks with which the company works and managerial ownership on operational performance. On the other hand, the number of banks with which the company maintains a relationship is positively conditioned by operational performance and negatively by managerial ownership. In turn, managerial ownership is negatively conditioned by operational performance and the nature of the banking relationship

Are There Non-linear Effects of Banking Relationships and Ownership Concentration on Operational Performance? Empirical Evidence from Portuguese SMEs Using Cross-section Analysis and Panel Data

This paper provides new evidence for the relationship between the stability of the banking relationship, ownership concentration and operating profitability, supporting non-linear effects between those variables in the context of small and medium enterprises (SMEs). From a sample of 4,163 Portuguese SMEs and cross-section data and panel data, we found evidence for a U-shaped quadratic relationship between the stability of the banking relationship and operational performance. This result indicates that the consolidation of new banking relationships, the difficulties experienced by SMEs in overcoming the problems of adverse selection and moral hazard reflect negatively on their operating profitability. However, when the banking relationship is solidified, and banking institutions acquire information, supervision and monitoring costs decrease, credit constraints are lower and contractual conditions are tailored to the needs of the company, with positive impacts on operating profitability. In turn, the quadratic specification established between ownership concentration and operating profitability suggests that the expropriation hypothesis prevails for low levels of control rights and the supervision hypothesis prevails for high levels

Extração de conhecimento a partir de fontes semi-estruturadas

The increasing number of small, cheap devices, full of sensing capabilities lead to an untapped source of data that can be explored to improve and optimize multiple systems, from small-scale home automation to large-scale applications such as agriculture monitoring, traffic flow and industrial maintenance prediction. Yet, hand in hand with this growth, goes the increasing difficulty to collect, store and organize all these new data. The lack of standard context representation schemes is one of the main struggles in this area. Furthermore, conventional methods for extracting knowledge from data rely on standard representations or a priori relations. These a priori relations add latent information to the underlying model, in the form of context representation schemes, table relations, or even ontologies. Nonetheless, these relations are created and maintained by human users. While feasible for small-scale scenarios or specific areas, this becomes increasingly difficult to maintain when considering the potential dimension of IoT and M2M scenarios. This thesis addresses the problem of storing and organizing context information from IoT/M2M scenarios in a meaningful way, without imposing a representation scheme or requiring a priori relations. This work proposes a d-dimension organization model, which was optimized for IoT/M2M data. The model relies on machine learning features to identify similar context sources. These features are then used to learn relations between data sources automatically, providing the foundations for automatic knowledge extraction, where machine learning, or even conventional methods, can rely upon to extract knowledge on a potentially relevant dataset. During this work, two different machine learning techniques were tackled: semantic and stream similarity. Semantic similarity estimates the similarity between concepts (in textual form). This thesis proposes an unsupervised learning method for semantic features based on distributional profiles, without requiring any specific corpus. This allows the organizational model to organize data based on concept similarity instead of string matching. Another advantage is that the learning method does not require input from users, making it ideal for massive IoT/M2M scenarios. Stream similarity metrics estimate the similarity between two streams of data. Although these methods have been extensively researched for DNA sequencing, they commonly rely on variants of the longest common sub-sequence. This PhD proposes a generative model for stream characterization, specially optimized for IoT/M2M data. The model can be used to generate statistically significant data’s streams and estimate the similarity between streams. This is then used by the context organization model to identify context sources with similar stream patterns. The work proposed in this thesis was extensively discussed, developed and published in several international publications. The multiple contributions in projects and collaborations with fellow colleagues, where parts of the work developed were used successfully, support the claim that although the context organization model (and subsequent similarity features) were optimized for IoT/M2M data, they can potentially be extended to deal with any kind of context information in a wide array of applications.O número crescente de dispositivos pequenos e baratos, repletos de capacidades sensoriais, criou uma nova fonte de dados que pode ser explorada para melhorar e otimizar vários sistemas, desde domótica em ambientes residenciais até aplicações de larga escala como monitorização agrícola, gestão de tráfego e manutenção preditiva a nível industrial. No entanto, este crescimento encontra-se emparelhado com a crescente dificuldade em recolher, armazenar e organizar todos estes dados. A inexistência de um esquema de representação padrão é uma das principais dificuldades nesta área. Além disso, métodos de extração de conhecimento convencionais dependem de representações padrão ou relações definidas a priori. No entanto estas relações são definidas e mantidas por utilizadores humanos. Embora seja viável para cenários de pequena escala ou áreas especificas, este tipo de relações torna-se cada vez mais difícil de manter quando se consideram cenários com a dimensão associado a IoT e M2M. Esta tese de doutoramento endereça o problema de armazenar e organizar informação de contexto de cenários de IoT/M2M, sem impor um esquema de representação ou relações a priori. Este trabalho propõe um modelo de organização com d dimensões, especialmente otimizado para dados de IoT/M2M. O modelo depende de características de machine learning para identificar fontes de contexto similares. Estas caracteristicas são utilizadas para aprender relações entre as fontes de dados automaticamente, criando as fundações para a extração de conhecimento automática. Quer machine learning quer métodos convencionais podem depois utilizar estas relações automáticas para extrair conhecimento em datasets potencialmente relevantes. Durante este trabalho, duas técnicas foram desenvolvidas: similaridade semântica e similaridade entre séries temporais. Similaridade semântica estima a similaridade entre conceitos (em forma textual). Este trabalho propõe um método de aprendizagem não supervisionado para features semânticas baseadas em perfis distributivos, sem exigir nenhum corpus específico. Isto permite ao modelo de organização organizar dados baseado em conceitos e não em similaridade de caracteres. Numa outra vantagem importante para os cenários de IoT/M2M, o método de aprendizagem não necessita de dados de entrada adicionados por utilizadores. A similaridade entre séries temporais são métricas que permitem estimar a similaridade entre várias series temporais. Embora estes métodos tenham sido extensivamente desenvolvidos para sequenciação de ADN, normalmente dependem de variantes de métodos baseados na maior sub-sequencia comum. Esta tese de doutoramento propõe um modelo generativo para caracterizar séries temporais, especialmente desenhado para dados IoT/M2M. Este modelo pode ser usado para gerar séries temporais estatisticamente corretas e estimar a similaridade entre múltiplas séries temporais. Posteriormente o modelo de organização identifica fontes de contexto com padrões temporais semelhantes. O trabalho proposto foi extensivamente discutido, desenvolvido e publicado em diversas publicações internacionais. As múltiplas contribuições em projetos e colaborações com colegas, onde partes trabalho desenvolvido foram utilizadas com sucesso, permitem reivindicar que embora o modelo (e subsequentes técnicas) tenha sido otimizado para dados IoT/M2M, podendo ser estendido para lidar com outros tipos de informação de contexto noutras áreas.The present study was developed in the scope of the Smart Green Homes Project [POCI-01-0247-FEDER-007678], a co-promotion between Bosch Termotecnologia S.A. and the University of Aveiro. It is financed by Portugal 2020 under the Competitiveness and Internationalization Operational Program, and by the European Regional Development Fund.Programa Doutoral em Informátic

A comparative analysis of financing decisions in export and non-export sectors : the case of Spanish non-listed firms

Esta tese tem como objetivo estudar as diferenças nas decisões de financiamento entre as empresas exportadoras e não-exportadoras não cotadas em Espanha e, também, examinar qual é o impacto da intensidade de exportação no nível de endividamento das mesmas empresas. Para isso, usamos uma amostra composta por 45 147 empresas, durante o período de 2012 a 2017. Após uma revisão detalhada da literatura, foi feita uma análise usando diferentes determinantes que, de acordo com a literatura existente, têm impacto na estrutura de capital das empresas (e consequentemente nas suas decisões de financiamento): Impostos, Tangibilidade, Rentabilidade, Dimensão da Empresa, Outros Benefícios Fiscais para além da Dívida, Condições da Indústria, Risco de Negócio, Oportunidades de Crescimento, Taxa de Inflação e Intensidade de Exportação. Os resultados obtidos sugerem que, embora alguns fatores estejam de acordo com a literatura existente, tal como o impacto dos Impostos, da Tangibilidade, da Rentabilidade, das Condições de Indústria, do Risco de Negócio e da Taxa de Inflação; a Dimensão da Empresa e os Outros Benefícios Fiscais para além da Dívida apresentam impactos no nível da dívida diferentes dos esperados. Para além disso, o único fator cujos resultados diferem das empresas exportadoras para as empresas não exportadoras são os Impostos, que apresenta um impacto negativo na alavancagem para empresas exportadoras e positivo para com as não exportadoras. Finalmente, verifica-se que a Intensidade de Exportação tem uma relação positiva com o nível de endividamento.The purpose of this thesis is to study the differences in the financing decisions between non-listed Spanish export and non-export firms, as well as to examine what is the impact of export intensity in firm’s leverage. To do so, we use a sample of 45,147 Spanish unlisted firms during the 2012-2017 period. After a detailed literature review, an analysis was made using different determinants that, according to the extant literature, impact the capital structure (and consequently, the financing decisions): Taxes, Tangibility, Profitability, Firm Size, Non-Debt Tax Shields, Industry Conditions, Business Risk, Growth Opportunities, Inflation Rate and Export Intensity. The results obtained suggest that while the impact of some factors are in line with the extant literature, namely Taxes, Tangibility, Profitability, Industry Conditions, Business Risk and Inflation Rate; the impact of Firm Size and Non-Debt Tax Shields is different from what we expected. Furthermore, the only factor that affects differently both export and non-export firms is Taxes, which presents a negative correlation with export firms’ leverage and positive with non-export firms’ leverage. Finally, the variable Export Intensity shows a positive relationship with Leverage

Viral hepatitis : a national problem

As hepatites virais constituem um complexo de doenças com pelo menos cinco agentes, quais sejam as hepatites A e B, duas formas de hepatite não-A/não-B e as infecções pelo agente delta. Grandes segmentos de nossa população são infectados por estes agentes a cada ano, com um enorme impacto nos sistemas de saúde e na própria economia nacional. Informações confiáveis sobre a incidência e a prevalência das hepatites são de difícil obtenção pela alta incidência de infecções subclínicas, a falta de um sistema de notificação adequado e a não confirmação laboratorial das infecções, pelo alto custo dos reativos para diagnóstico laboratorial, em sua grande maioria ainda importados.Viral hepatitis is a complex entity caused by at least five agents namely hepatitis viruses A and B, two forms of hepatitis non A/non B and agent delta. Large numbers of our population are infected yearly by these viruses causing an enormous impact on our health system and the national economy. Realiable information on the incidence and prevalence of hepatitis is difficult to obtain due to the high incidence of subclinical infections and the absence of an adequate system of notifications. Laboratory confirmation is frequently lacking due to the high cost of diagnostic reagents which usually have to be imported

Onchocerciasis: new foci in Brazil?

O recente achado de um caso autóctone de oncocercose no Estado de Goiás - assinalando, talvez, a existência de um novo foco da doença no Brasil - veio confirmar sobre o perigo em potencial, para o resto do País