Enhancing the selection of a model-based clustering with external categorical variables

In cluster analysis, it can be useful to interpret the partition built from the data in the light of external categorical variables which are not directly involved to cluster the data. An approach is proposed in the model-based clustering context to select a number of clusters which both fits the data well and takes advantage of the potential illustrative ability of the external variables. This approach makes use of the integrated joint likelihood of the data and the partitions at hand, namely the model-based partition and the partitions associated to the external variables. It is noteworthy that each mixture model is fitted by the maximum likelihood methodology to the data, excluding the external variables which are used to select a relevant mixture model only. Numerical experiments illustrate the promising behaviour of the derived criterion. © 2014 Springer-Verlag Berlin Heidelberg.

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.

O papel do educador na promoção do envolvimento parental: uma reflexão

Relatório da Prática Profissional Supervisionada Mestrado em Educação Pré-Escolar

Envolvimento parental na ação educativa escolar

Relatório de Estágio apresentado à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ensino do 1.º e 2.º Ciclo do Ensino Básico

The effects of parental sensitivity and involvement in caregiving on mother–infant and father–infant attachment in a portuguese sample

In the present longitudinal study, we investigated attachment quality in Portuguese mother–infant and in father–infant dyads, and evaluated whether attachment quality was related to parental sensitivity during parent–infant social interaction or to the amount of time each parent spent with the infant during play and in routine caregiving activities (e.g., feeding, bathing, play). The sample consisted of 82 healthy full-term infants (30 girls, 53 boys, 48 first born), and their mothers and fathers from mostly middle-class households. To assess parental sensitivity, mothers and fathers were independently observed during free play interactions with their infants when infants were 9 and 15 months old. The videotaped interactions were scored by masked coders using the Crittenden’s CARE-Index. When infants were 12 and 18 months old, mother–infant and father–infant dyads were videotaped during an adaptation of Ainsworth’s Strange Situation. Parents also described their level of involvement in infant caregiving activities using a Portuguese version of the McBride and Mills Parent Responsibility Scale. Mothers were rated as being more sensitive than fathers during parent–infant free play at both 9 and 15 months. There also was a higher prevalence of secure attachment in mother–infant versus father–infant dyads at both 12 and 18 months. Attachment security was predicted by the amount of time mothers and fathers were involved in caregiving and play with the infant, and with parents’ behavior during parent–infant free play.

The role of the efflux mechanisms in multidrug resistance in Mycobacterium tuberculosis

Abstract The emergence of multi and extensively drug resistant tuberculosis (MDRTB and XDRTB) has increased the concern of public health authorities around the world. The World Health Organization has defined MDRTB as tuberculosis (TB) caused by organisms resistant to at least isoniazid and rifampicin, the main first-line drugs used in TB therapy, whereas XDRTB refers to TB resistant not only to isoniazid and rifampicin, but also to a fluoroquinolone and to at least one of the three injectable second-line drugs, kanamycin, amikacin and capreomycin. Resistance in Mycobacterium tuberculosis is mainly due to the occurrence of spontaneous mutations and followed by selection of mutants by subsequent treatment. However, some resistant clinical isolates do not present mutations in any genes associated with resistance to a given antibiotic, which suggests that other mechanism(s) are involved in the development of drug resistance, namely the presence of efflux pump systems that extrude the drug to the exterior of the cell, preventing access to its target. Increased efflux activity can occur in response to prolonged exposure to subinhibitory concentrations of anti-TB drugs, a situation that may result from inadequate TB therapy. The inhibition of efflux activity with a non-antibiotic inhibitor may restore activity of an antibiotic subject to efflux and thus provide a way to enhance the activity of current anti-TB drugs. The work described in this thesis foccus on the study of efflux mechanisms in the development of multidrug resistance in M. tuberculosis and how phenotypic resistance, mediated by efflux pumps, correlates with genetic resistance. In order to accomplish this goal, several experimental protocols were developed using biological models such as Escherichia coli, the fast growing mycobacteria Mycobacterium smegmatis, and Mycobacterium avium, before their application to M. tuberculosis. This approach allowed the study of the mechanisms that result in the physiological adaptation of E. coli to subinhibitory concentrations of tetracycline (Chapter II), the development of a fluorometric method that allows the detection and quantification of efflux of ethidium bromide (Chapter III), the characterization of the ethidium bromide transport in M. smegmatis (Chapter IV) and the contribution of efflux activity to macrolide resistance in Mycobacterium avium complex (Chapter V). Finally, the methods developed allowed the study of the role of efflux pumps in M. tuberculosis strains induced to isoniazid resistance (Chapter VI). By this manner, in Chapter II it was possible to observe that the physiological adaptation of E. coli to tetracycline results from an interplay between events at the genetic level and protein folding that decrease permeability of the cell envelope and increase efflux pump activity. Furthermore, Chapter III describes the development of a semi-automated fluorometric method that allowed the correlation of this efflux activity with the transport kinetics of ethidium bromide (a known efflux pump substrate) in E. coli and the identification of efflux inhibitors. Concerning M. smegmatis, we have compared the wild-type M. smegmatis mc2155 with knockout mutants for LfrA and MspA for their ability to transport ethidium bromide. The results presented in Chapter IV showed that MspA, the major porin in M. smegmatis, plays an important role in the entrance of ethidium bromide and antibiotics into the cell and that efflux via the LfrA pump is involved in low-level resistance to these compounds in M. smegmatis. Chapter V describes the study of the contribution of efflux pumps to macrolide resistance in clinical M. avium complex isolates. It was demonstrated that resistance to clarithromycin was significantly reduced in the presence of efflux inhibitors such as thioridazine, chlorpromazine and verapamil. These same inhibitors decreased efflux of ethidium bromide and increased the retention of [14C]-erythromycin in these isolates. Finaly, the methods developed with the experimental models mentioned above allowed the study of the role of efflux pumps on M. tuberculosis strains induced to isoniazid resistance. This is described in Chapter VI of this Thesis, where it is demonstrated that induced resistance to isoniazid does not involve mutations in any of the genes known to be associated with isoniazid resistance, but an efflux system that is sensitive to efflux inhibitors. These inhibitors decreased the efflux of ethidium bromide and also reduced the minimum inhibitory concentration of isoniazid in these strains. Moreover, expression analysis showed overexpression of genes that code for efflux pumps in the induced strains relatively to the non-induced parental strains. In conclusion, the work described in this thesis demonstrates that efflux pumps play an important role in the development of drug resistance, namely in mycobacteria. A strategy to overcome efflux-mediated resistance may consist on the use of compounds that inhibit efflux activity, restoring the activity of antimicrobials that are efflux pump substrates, a useful approach particularly in TB where the most effective treatment regimens are becoming uneffective due to the increase of MDRTB/XDRTB.

Enhancing the selection of a model-based clustering with external categorical variables

In cluster analysis, it can be useful to interpret the partition built from the data in the light of external categorical variables which are not directly involved to cluster the data. An approach is proposed in the model-based clustering context to select a number of clusters which both fits the data well and takes advantage of the potential illustrative ability of the external variables. This approach makes use of the integrated joint likelihood of the data and the partitions at hand, namely the model-based partition and the partitions associated to the external variables. It is noteworthy that each mixture model is fitted by the maximum likelihood methodology to the data, excluding the external variables which are used to select a relevant mixture model only. Numerical experiments illustrate the promising behaviour of the derived criterion.

Materials selection for a set of multiple parts considering manufacturing costs and weight reduction with structural isoperformance using direct multisearch optimization

Materials selection is a matter of great importance to engineering design and software tools are valuable to inform decisions in the early stages of product development. However, when a set of alternative materials is available for the different parts a product is made of, the question of what optimal material mix to choose for a group of parts is not trivial. The engineer/designer therefore goes about this in a part-by-part procedure. Optimizing each part per se can lead to a global sub-optimal solution from the product point of view. An optimization procedure to deal with products with multiple parts, each with discrete design variables, and able to determine the optimal solution assuming different objectives is therefore needed. To solve this multiobjective optimization problem, a new routine based on Direct MultiSearch (DMS) algorithm is created. Results from the Pareto front can help the designer to align his/hers materials selection for a complete set of materials with product attribute objectives, depending on the relative importance of each objective.

Welfare regimes, work-life balance public policies and gender equality - parental leaves in Portugal and Sweden

Comunicação apresentada na "European Sociological Association Conference" em Lisboa de 2 a 5 de Setembro de 2009.

Exploiting the bin-class histograms for feature selection on discrete data

In machine learning and pattern recognition tasks, the use of feature discretization techniques may have several advantages. The discretized features may hold enough information for the learning task at hand, while ignoring minor fluctuations that are irrelevant or harmful for that task. The discretized features have more compact representations that may yield both better accuracy and lower training time, as compared to the use of the original features. However, in many cases, mainly with medium and high-dimensional data, the large number of features usually implies that there is some redundancy among them. Thus, we may further apply feature selection (FS) techniques on the discrete data, keeping the most relevant features, while discarding the irrelevant and redundant ones. In this paper, we propose relevance and redundancy criteria for supervised feature selection techniques on discrete data. These criteria are applied to the bin-class histograms of the discrete features. The experimental results, on public benchmark data, show that the proposed criteria can achieve better accuracy than widely used relevance and redundancy criteria, such as mutual information and the Fisher ratio.

The selection of senior civil servants in the context of the different public administration models: an issue of accountability

Comunicação apresentada no Congresso do IIAS-IISA no âmbito do IX Grupo de Estudo: Serviço público e política, realizado em Ifrane, Marrocos de 13 a 17 de junho de 2014

Finding a school technological partner: a multicriteria method for school information system producer selection

The choice of an information systems is a critical factor of success in an organization's performance, since, by involving multiple decision-makers, with often conflicting objectives, several alternatives with aggressive marketing, makes it particularly complex by the scope of a consensus. The main objective of this work is to make the analysis and selection of a information system to support the school management, pedagogical and administrative components, using a multicriteria decision aid system – MMASSITI – Multicriteria Method- ology to Support the Selection of Information Systems/Information Technologies – integrates a multicriteria model that seeks to provide a systematic approach in the process of choice of Information Systems, able to produce sustained recommendations concerning the decision scope. Its application to a case study has identi- fied the relevant factors in the selection process of school educational and management information system and get a solution that allows the decision maker’ to compare the quality of the various alternatives.

Group decision making for selection of an information system in a business context

The main objective of this work is to report on the development of a multi-criteria methodology to support the assessment and selection of an Information System (IS) framework in a business context. The objective is to select a technological partner that provides the engine to be the basis for the development of a customized application for shrinkage reduction on the supply chains management. Furthermore, the proposed methodology di ers from most of the ones previously proposed in the sense that 1) it provides the decision makers with a set of pre-defined criteria along with their description and suggestions on how to measure them and 2)it uses a continuous scale with two reference levels and thus no normalization of the valuations is required. The methodology here proposed is has been designed to be easy to understand and use, without a specific support of a decision making analyst.

Expatriates recruitment and selection for long-term international assignments in portuguese companies

Long-term international assignments’ increase requires more attention being paid for the preparation of these foreign assignments, especially on the recruitment and selection process of expatriates. This article explores how the recruitment and selection process of expatriates is developed in Portuguese companies, examining the main criteria on recruitment and selection of expatriates’ decision to send international assignments. The paper is based on qualitative case studies of companies located in Portugal. The data were collected through semi-structured interviews of 42 expatriates and 18 organisational representatives as well from nine Portuguese companies. The findings show that the most important criteria are: (1) trust from managers, (2) years in service, (3) previous technical and language competences, (4) organisational knowledge and, (5) availability. Based on the findings, the article discusses in detail the main theoretical and managerial implications. Suggestions for further research are also presented.