Organização do trabalho doméstico em casais do mesmo sexo

Em resposta ao predomínio da heteronormatividade nos estudos sobre o trabalho doméstico, este artigo explora a forma como este é organizado e distribuído em casais do mesmo sexo. Para esse efeito, desenvolveu-se uma pesquisa qualitativa (20 entrevistas aos membros de casais homossexuais) em torno dos desequilíbrios, do processo de negociação, do nível de satisfação, e ainda da herança familiar genderizada na actual organização do trabalho doméstico. Concluiu-se que a ausência da diferença de sexo no casal contribui para uma mais flexível e paritária negociação da organização das tarefas. Reflexo da socialização de género, as mulheres tendem para uma maior especialização e os homens para uma maior delegação das tarefas. In response to the predominance of heteronormativity in the studies on the household labour, this article explores the way it is organized and distributed in same-sex couples. Qualitative research was carried out on the basis of 20 interviews with members of homosexual couples, and informationwas collected on the imbalances, negotiation, satisfaction and gendered family legacy in the current organization of household labour. Results show that the absence of the sex difference between the members of the couple contributes to more flexible and egalitarian negotiation in the organization of chores. As a consequence of gender socialization, women tend to specialize and men to delegate.

Arrow Plot: a new graphical tool for selecting up and down regulated genes and genes differentially expressed on samples subgroups

Background: A common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software. Results: This method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes. Conclusion: Our results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.

Acompanhamento dos trabalhos de reabilitação de espaços exteriores à Casa Museu dos Patudos e edifício de apoio: Câmara Municipal de Alpiarça

Relatório de Estágio para obtenção de grau de Mestre em Engenharia Civil Perfil de Edificações

Leonel Duarte Ferreira (1894-1959) : vida e obra musical

Tese apresentada para o cumprimento dos requisitos necessários à obtenção do grau de Doutor no ramo de Ciências Musicais

Parallel implementation of vertex component analysis for hyperspectral endmember extraction

International Conference with Peer Review 2012 IEEE International Conference in Geoscience and Remote Sensing Symposium (IGARSS), 22-27 July 2012, Munich, Germany

The organ verses of Frei Jerónimo da Madre de Deus: Portuguese organ music in the time of D. João V

Contrastando com o importante legado dos mestres organistas portugueses dos séculos XVI e XVII, a música portuguesa para órgão pós-1700 parece quase inexistente (excluindo raros exemplos, como as quatro sonatas para órgão de Carlos Seixas). Seja devido à destruição causada pelo grande terramoto de Lisboa em 1755, ou a outras causas, a ausência de fontes é surpreendente, considerando os testemunhos de actividade musical durante aquele período. Este artigo lida com uma fonte até hoje relativamente ignorada: o manuscrito CLI/1-4 nº 7 da Biblioteca do Palácio Ducal de Vila Viçosa (Versos / Sobre o Canto Chão / Para Orgão / De Fr. Jeronimo da M.dre de DS.). Esta colecção de vinte versos para órgão de Jerónimo da Madre de Deus é, de longe, a maior obra portuguesa para órgão da primeira metade do século XVIII até hoje conhecida. Claramente pensadas para o órgão, estas curtas peças testemunham a transformação da escrita para tecla em Portugal durante o reinado de D. João V (nomeadamente através da absorção de influências italianas) e fornecem informações preciosas sobre o tipo de instrumento em que eram tocadas.

Determining the number of clusters in categorical data

Cluster analysis for categorical data has been an active area of research. A well-known problem in this area is the determination of the number of clusters, which is unknown and must be inferred from the data. In order to estimate the number of clusters, one often resorts to information criteria, such as BIC (Bayesian information criterion), MML (minimum message length, proposed by Wallace and Boulton, 1968), and ICL (integrated classification likelihood). In this work, we adopt the approach developed by Figueiredo and Jain (2002) for clustering continuous data. They use an MML criterion to select the number of clusters and a variant of the EM algorithm to estimate the model parameters. This EM variant seamlessly integrates model estimation and selection in a single algorithm. For clustering categorical data, we assume a finite mixture of multinomial distributions and implement a new EM algorithm, following a previous version (Silvestre et al., 2008). Results obtained with synthetic datasets are encouraging. The main advantage of the proposed approach, when compared to the above referred criteria, is the speed of execution, which is especially relevant when dealing with large data sets.

Beyond methodological nationalism: The contribution of Robert E. Park to the history of intercultural communication

The legacy of nineteenth century social theory followed a “nationalist” model of society, assuming that analysis of social realities depends upon national boundaries, taking the nation-state as the primary unit of analysis, and developing the concept of methodological nationalism. This perspective regarded the nation-state as the natural - and even necessary - form of society in modernity. Thus, the constitution of large cities, at the end of the 19th century, through the intense flows of immigrants coming from diverse political and linguistic communities posed an enormous challenge to all social research. One of the most significant studies responding to this set of issues was The Immigrant Press and its Control, by Robert E. Park, one of the most prominent American sociologists of the first half of the 20th century. The Immigrant Press and its Control was part of a larger project entitled Americanization Studies: The Acculturation of Immigrant Group into American Society, funded by the Carnagie Corporation following World War I, taking as its goal to study the so-called “Americanization methods” during the 1920s. This paper revisits that particular work by Park to reveal how his detailed analysis of the role of the immigrant press overcame the limitations of methodological nationalism. By granting importance to language as a tool uniting each community and by showing how the strength of foreign languages expressed itself through the immigrant press, Park demonstrated that the latter produces a more ambivalent phenomenon than simply the assimilation of immigrants. On the one hand, the immigrant press served as a connecting force, driven by the desire to preserve the mother tongue and culture while at the same time awakening national sentiments that had, until then, remained diffuse. Yet, on the other hand, it facilitated the adjustment of immigrants to the American context. As a result, Park’s work contributes to our understanding of a particular liminal moment inherent within many intercultural contexts, the space between emigrant identity (emphasizing the country of origin) and immigrant identity (emphasizing the newly adopted country). His focus on the role played by media in the socialization of immigrant groups presaged later work on this subject by communication scholars. Focusing attention on Park’s research leads to other studies of the immigrant experience from the same period (e.g., Thomas & Znaniecki, The Polish Peasant in Europe and America), and also to insights on multi-presence and interculturality as significant but often overlooked phenomena in the study of immigrant socialization.

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

Integrated analysis of climate, soil, topography and vegetative growth in Iberian viticultural regions

The Iberian viticultural regions are convened according to the Denomination of Origin (DO) and present different climates, soils, topography and management practices. All these elements influence the vegetative growth of different varieties throughout the peninsula, and are tied to grape quality and wine type. In the current study, an integrated analysis of climate, soil, topography and vegetative growth was performed for the Iberian DO regions, using state-of-the-art datasets. For climatic assessment, a categorized index, accounting for phenological/thermal development, water availability and grape ripening conditions was computed. Soil textural classes were established to distinguish soil types. Elevation and aspect (orientation) were also taken into account, as the leading topographic elements. A spectral vegetation index was used to assess grapevine vegetative growth and an integrated analysis of all variables was performed. The results showed that the integrated climate-soil-topography influence on vine performance is evident. Most Iberian vineyards are grown in temperate dry climates with loamy soils, presenting low vegetative growth. Vineyards in temperate humid conditions tend to show higher vegetative growth. Conversely, in cooler/warmer climates, lower vigour vineyards prevail and other factors, such as soil type and precipitation acquire more important roles in driving vigour. Vines in prevailing loamy soils are grown over a wide climatic diversity, suggesting that precipitation is the primary factor influencing vigour. The present assessment of terroir characteristics allows direct comparison among wine regions and may have great value to viticulturists, particularly under a changing climate.

Check your biosignals here: a new dataset for off-person ECG biometrics

The Check Your Biosignals Here initiative (CYBHi) was developed as a way of creating a dataset and consistently repeatable acquisition framework, to further extend research in electrocardiographic (ECG) biometrics. In particular, our work targets the novel trend towards off-the-person data acquisition, which opens a broad new set of challenges and opportunities both for research and industry. While datasets with ECG signals collected using medical grade equipment at the chest can be easily found, for off-the-person ECG data the solution is generally for each team to collect their own corpus at considerable expense of resources. In this paper we describe the context, experimental considerations, methods, and preliminary findings of two public datasets created by our team, one for short-term and another for long-term assessment, with ECG data collected at the hand palms and fingers. (C) 2013 Elsevier Ireland Ltd. All rights reserved.

Paired indices for clustering evaluation correction for agreement by chance

In the present paper we focus on the performance of clustering algorithms using indices of paired agreement to measure the accordance between clusters and an a priori known structure. We specifically propose a method to correct all indices considered for agreement by chance - the adjusted indices are meant to provide a realistic measure of clustering performance. The proposed method enables the correction of virtually any index - overcoming previous limitations known in the literature - and provides very precise results. We use simulated datasets under diverse scenarios and discuss the pertinence of our proposal which is particularly relevant when poorly separated clusters are considered. Finally we compare the performance of EM and KMeans algorithms, within each of the simulated scenarios and generally conclude that EM generally yields best results.

An unsupervised approach to feature discretization and selection

Many learning problems require handling high dimensional datasets with a relatively small number of instances. Learning algorithms are thus confronted with the curse of dimensionality, and need to address it in order to be effective. Examples of these types of data include the bag-of-words representation in text classification problems and gene expression data for tumor detection/classification. Usually, among the high number of features characterizing the instances, many may be irrelevant (or even detrimental) for the learning tasks. It is thus clear that there is a need for adequate techniques for feature representation, reduction, and selection, to improve both the classification accuracy and the memory requirements. In this paper, we propose combined unsupervised feature discretization and feature selection techniques, suitable for medium and high-dimensional datasets. The experimental results on several standard datasets, with both sparse and dense features, show the efficiency of the proposed techniques as well as improvements over previous related techniques.

Efficient feature selection filters for high-dimensional data

Feature selection is a central problem in machine learning and pattern recognition. On large datasets (in terms of dimension and/or number of instances), using search-based or wrapper techniques can be cornputationally prohibitive. Moreover, many filter methods based on relevance/redundancy assessment also take a prohibitively long time on high-dimensional. datasets. In this paper, we propose efficient unsupervised and supervised feature selection/ranking filters for high-dimensional datasets. These methods use low-complexity relevance and redundancy criteria, applicable to supervised, semi-supervised, and unsupervised learning, being able to act as pre-processors for computationally intensive methods to focus their attention on smaller subsets of promising features. The experimental results, with up to 10(5) features, show the time efficiency of our methods, with lower generalization error than state-of-the-art techniques, while being dramatically simpler and faster.

‘Thy love afar is spite at home' Emerson, Thoreau and Carey: an alternative perspective of communication in US

The conquest of the West by the stagecoaches and then by railway, Ford and the automobile civilization, the Moon landing by Apollo 11, Microsoft, Apple, CNN, Google and Facebook have appeared to us as celebratory examples of the willingness and ability of the US to overcome the distance and the absence through so-called modern progress of transportation and communication. Undoubtedly, the imaginary and the instrumental power associated to transports and communication of the last century and a half are identified with the mental images that the world has of the US. A world that has eagerly imported and copy their technology and technological culture. Beyond the illusions, this attempting, which has always been praised to transcende space and eclipse the time to get to places and peole increasingly distant and fast, has always a dark side: the political control of population, commercial advertising, the spread of the rumors, noise and gossip. However, since at least the nineteenth century, the political project incorporated in modern transportation and communication technologies was not shared by some of the most remarkable thinkers in the US not only in that century, but also in the 20th century. This paper begins by rescue Ralph W. Emerson and Henry D. Thoreau legacy regarding to communication. Emerson conceived communication as a give-and-take with no coordination between the two, and does not involve contact with the other. Thoreau, in turn, argued that modern trasnportation and communications inventions are but pretty toys which distract attention from serious things, nothing more than 'improved means to an end that is not perfected.' Secondly, we show that this skeptical view of the techological improvement of transport and communication was proceed in an original way with James W. Carey, a media studies thinker who became known for his criticism of the transmission view of communication.