Suchergebnisse

A significant part of the field of migration studies has been filled by theoretical-empirical debates around a characterization, which is also valuable, of the different models of the political framework of migratory phenomena. However, more or less close to the assimilationist, multiculturalist or even interculturalist model, the main analytical proposals in this field are largely centred on a set of agrarian assumptions of the migrant actor, their characteristics and skills, which would eventually define the probabilities of a more or less favorable trajectory. But the need to identify explanatory variables and sociological sense for what are accepted as regularities within the category of nationality, reconfigured in the homogenizing idea of community, has left a small space to think about the impact of structural measures on the migratory reality. This article aims to problematize the importance of the State as an agent for the creation of public policies to consolidate the dynamics of social incorporation of migrant populations, and its consequences with regard to the production of ethnic identity in a spatio-temporal context and for two populations: the migrant population referred to as 'returnees'; and the migrant population of Indian origin. At the same time, the idea of consolidation of the Social State in the context of the public policies designed to frame the returned population as a consequence of the decolonization process is recovered. ; Uma parte significativa do campo de estudos de migrações tem sido preenchido por debates teórico-empíricos em torno de uma caracterização, que é também valorativa, dos diferentes modelos de enquadramento político dos fenómenos migratórios. Todavia, mais ou menos próximas do modelo assimilacionista, multiculturalista ou, até, interculturalista, as principais propostas analíticas neste campo centram-se largamente num conjunto de pressupostos agenciais do actor migrante, das suas características e competências, que, eventualmente, lhe definiriam as probabilidades de ...

With subprime mortgage crisis, Lehman Brothers Holdings Inc. bankruptcy and European government credit crisis, the CDS market assisted to a generalized turmoil, contributing for a decrease of CDS market in more than 50% in less than 3 years. This dissertation focuses on testing possible determinants of the basis spread for several European companies, analysing data between June 18 2008 and December 31 2012. All financial information and data used in this thesis was gathered from Bloomberg. Literature on single-name credit modelling and valuing credit derivatives is revised and applied to calculate the basis, with special focus on estimating hazard rates, where we used the optimization method instead of the generally used bootstrap method. We than, followed Zhu work and analysed the proposed determinants for the basis, updating his work by introducing two new variables as potential determinants of the basis: the CDS Big Bang and the Lehman Brothers bailout. Finally, we have found some evidence that efforts to standardize and regulate the credit derivative contracts, the CDS Big Bang has contributed to mitigate part of the counterpart risk, and that have also been reflected on the CDS-ASW basis.

Deformational plagiocephaly (DP) is a cranial deformity characterized by an asymmetrical distortion of an infant's skull. The diagnosis and evaluation of DP are performed using cranial asymmetry indexes obtained from cranial measurements, which can be estimated using anthropometric landmarks of the infant's head. However, manual labeling of these landmarks is a time-consuming and tedious task, being also prone to observer variability. In this paper, a novel framework to automatically detect anthropometric landmarks of 3D infant's head models is described. The proposed method is divided into two stages: (i) unfolding of the 3D head model surface; and (ii) landmarks' detection through a deep learning strategy. In the first stage, an unfolding strategy is used to transform the 3D mesh of the head model to a flattened 2D version of it. From the flattened mesh, three 2D informational maps are generated using specific head characteristics. In the second stage, a deep learning strategy is used to detect the anthropometric landmarks in a 3-channel image constructed using the combination of informational maps. The proposed framework was validated in fifteen 3D synthetic models of infant's head, being achieved, in average for all landmarks, a mean distance error of 3.5 mm between the automatic detection and a manually constructed ground-truth. Moreover, the estimated cranial measurements were comparable to the ones obtained manually, without statistically significant differences between them for most of the indexes. The obtained results demonstrated the good performance of the proposed method, showing the potential of this framework in clinical practice. ; This work was funded by the project NORTE-01-0145-FEDER-024300, supported by Northern Portugal Regional Operational Programme (Norte2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER). Moreover, this work has been also supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019. Furthermore, the authors acknowledge FCT, Portugal, and the European Social Found, European Union, for funding support through the "Programa Operacional Capital Humano" (POCH) in the scope of the PhD grants SFRH/BD/136670/2018 (Helena R. Torres), SFRH/BD/136721/2018 (Bruno Oliveira), and SFRH/BD/131545/2017 (Fernando Veloso).