The link between remittances and and education in Cape Verde

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

Corruption and Education: Empirical evidence from cross-country micro-data

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

Spatial Patterns and Irregularities of the electoral data: general elections in Canada

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

QBC® for the diagnosis of human and canine american visceral leishmaniasis: preliminary data

"Quantitative Buffy Coat" (QBC®) is a direct and fast fluorescent method used for the identification of blood parasites. Since Leishmania chagasi circulates in blood, we decided to test it in American visceral leishmaniasis (AVL). Bone marrow (BM) and peripheral blood (PB) of 49 persons and PB of 31 dogs were analyzed. QBC® was positive in BM of 11/11 patients with AVL and in 1/6 patients with other diseases. Amastigotes were identified in PB of 18/22 patients with AVL and in none without AVL. The test was positive in 30 out of the 31 seropositive dogs and in 28/28 dogs with Leishmania identified in other tissues. QBC® is a promising method for diagnosis of human AVL, and possibly for the exam of PB of patients with AVL/AIDS, for the control of the cure and for the identification of asymptomatic carriers. Because it is fast and easy to collect and execute, QBC® should be evaluated for programs of reservoir control.

Collecting data for indoor mapping of the university of Münster via a location based game

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Using epidemiological survey data to infer geographic distributions of leishmaniasis vector species

An important aspect of tropical medicine is analysis of geographic aspects of risk of disease transmission, which for lack of detailed public health data must often be reduced to an understanding of the distributions of critical species such as vectors and reservoirs. We examine the applicability of a new technique, ecological niche modeling, to the challenge of understanding distributions of such species based on municipalities in the state of São Paulo in which a group of 5 Lutzomyia sandfly species have been recorded. The technique, when tested based on independent occurrence data, yielded highly significant predictions of species' distributions; minimum sample sizes for effective predictions were around 40 municipalities.

Multivariate analysis applied to clinical analysis data

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

Data fusion with computational intelligence techniques: a case study of fuzzy inference for terrain assessment

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Evaluation and optimization of a session-based middleware for data management

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

A system’s approach to cache hierarchy-aware decomposition of data-parallel computations

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Combining WLAN fingerprint-based localization with sensor data for indoor navigation using mobile devices

This project proposes an approach for supporting Indoor Navigation Systems using Pedestrian Dead Reckoning-based methods and by analyzing motion sensor data available in most modern smartphones. Processes suggested in this investigation are able to calculate the distance traveled by a user while he or she is walking. WLAN fingerprint- based navigation systems benefit from the processes followed in this research and results achieved to reduce its workload and improve its positioning estimations.

Return Migration, Self-Selection and Entrepreneurship in Mozambique

Does return migration affect entrepreneurship? This question has important implications for the debate on the economic development effects of migration for origin countries. The existing literature has, however, not addressed how the estimation of the impact of return migration on entrepreneurship is affected by double unobservable migrant self-selection, both at the initial outward migration and at the final inward return migration stages. This paper uses a representative household survey conducted in Mozambique in order to address this research question. We exploit variation provided by displacement caused by civil war in Mozambique, as well as social unrest and other shocks in migrant destination countries. The results lend support to negative unobservable self-selection at both and each of the initial and return stages of migration, which results in an under-estimation of the effects of return migration on entrepreneurial outcomes when using a ‘naïve’ estimator not controlling for self-selection. Indeed, ‘naïve’ estimates point to a 13 pp increase in the probability of owning a business when there is a return migrant in the household relative to non-migrants only, whereas excluding the double effect of unobservable self-selection, this effect becomes significantly larger - between 24 pp and 29 pp, depending on the method of estimation and source of variation used.

Complex networks and data mining: toward a new perspective for the understanding of complex systems

Complex systems, i.e. systems composed of a large set of elements interacting in a non-linear way, are constantly found all around us. In the last decades, different approaches have been proposed toward their understanding, one of the most interesting being the Complex Network perspective. This legacy of the 18th century mathematical concepts proposed by Leonhard Euler is still current, and more and more relevant in real-world problems. In recent years, it has been demonstrated that network-based representations can yield relevant knowledge about complex systems. In spite of that, several problems have been detected, mainly related to the degree of subjectivity involved in the creation and evaluation of such network structures. In this Thesis, we propose addressing these problems by means of different data mining techniques, thus obtaining a novel hybrid approximation intermingling complex networks and data mining. Results indicate that such techniques can be effectively used to i) enable the creation of novel network representations, ii) reduce the dimensionality of analyzed systems by pre-selecting the most important elements, iii) describe complex networks, and iv) assist in the analysis of different network topologies. The soundness of such approach is validated through different validation cases drawn from actual biomedical problems, e.g. the diagnosis of cancer from tissue analysis, or the study of the dynamics of the brain under different neurological disorders.

Determinants of mother-baby relationship evaluated during pregnancy

ABSTRACT Background Mental health promotion is supported by a strong body of knowledge and is a matter of public health with the potential of a large impact on society. Mental health promotion programs should be implemented as soon as possible in life, preferably starting during pregnancy. Programs should focus on malleable determinants, introducing strategies to reduce risk factors or their impact on mother and child, and also on strengthening protective factors to increase resilience. The ambition of early detecting risk situations requires the development and use of tools to assess risk, and the creation of a responsive network of services based in primary health care, especially maternal consultation during pregnancy and the first months of the born child. The number of risk factors and the way they interact and are buffered by protective factors are relevant for the final impact. Maternal-fetal attachment (MFA) is not yet a totally understood and well operationalized concept. Methodological problems limit the comparison of data as many studies used small size samples, had an exploratory character or used different selection criteria and different measures. There is still a lack of studies in high risk populations evaluating the consequences of a weak MFA. Instead, the available studies are not very conclusive, but suggest that social support, anxiety and depression, self-esteem and self-control and sense of coherence are correlated with MFA. MFA is also correlated with health practices during pregnancy, that influence pregnancy and baby outcomes. MFA seems a relevant concept for the future mother baby interaction, but more studies are needed to clarify the concept and its operationalization. Attachment is a strong scientific concept with multiple implications for future child development, personality and relationship with others. Secure attachment is considered an essential basis of good mental health, and promoting mother-baby interaction offers an excellent opportunity to intervention programmes targeted at enhancing mental health and well-being. Understanding the process of attachment and intervening to improve attachment requires a comprehension of more proximal factors, but also a broader approach that assesses the impact of more distal social conditions on attachment and how this social impact is mediated by family functioning and mother-baby interaction. Finally, it is essential to understand how this knowledge could be translated in effective mental health promoting interventions and measures that could reach large populations of pregnant mothers and families. Strengthening emotional availability (EA) seems to be a relevant approach to improve the mother-baby relationship. In this review we have offered evidence suggesting a range of determinants of mother-infant relationship, including age, marital relationship, social disadvantages, migration, parental psychiatric disorders and the situations of abuse or neglect. Based on this theoretical background we constructed a theoretical model that included proximal and distal factors, risk and protective factors, including variables related to the mother, the father, their social support and mother baby interaction from early pregnancy until six months after birth. We selected the Antenatal Psychosocial Health Assessment (ALPHA) for use as an instrument to detect psychosocial risk during pregnancy. Method Ninety two pregnant women were recruited from the Maternal Health Consultation in Primary Health Care (PHC) at Amadora. They had three moments of assessment: at T1 (until 12 weeks of pregnancy) they filed out a questionnaire that included socio-demographic data, ALPHA, Edinburgh post-natal Depression Scale (EDPS), General Health Questionnaire (GHQ) and Sense of Coherence (SOC); at T2 (after the 20th weeks of pregnancy) they answered EDPS, SOC and MFA Scale (MFAS), and finally at T3 (6 months after birth), they repeated EDPS and SOC, and their interaction with their babies was videotaped and later evaluated using EA Scales. A statistical analysis has been done using descriptive statistics, correlation analysis, univariate logistic regression and multiple linear regression. Results The study has increased our knowledge on this particular population living in a multicultural, suburb community. It allow us to identify specific groups with a higher level of psychosocial risk, such as single or divorced women, young couples, mothers with a low level of education and those who are depressed or have a low SOC. The hypothesis that psychosocial risk is directly correlated with MFAS and that MFA is directly correlated with EA was not confirmed, neither the correlation between prenatal psychosocial risk and mother-baby EA. The study identified depression as a relevant risk factor in pregnancy and its higher prevalence in single or divorced women, immigrants and in those who have a higher global psychosocial risk. Depressed women have a poor MFA, and a lower structuring capacity and a higher hostility to their babies. In average, depression seems to reduce among pregnant women in the second part of their pregnancy. The children of immigrant mothers show a lower level of responsiveness to their mothers what could be transmitted through depression, as immigrant mothers have a higher risk of depression in the beginning of pregnancy and six months after birth. Young mothers have a low MFA and are more intrusive. Women who have a higher level of education are more sensitive and their babies showed to be more responsive. Women who are or have been submitted to abuse were found to have a higher level of MFA but their babies are less responsive to them. The study highlights the relevance of SOC as a potential protective factor while it is strongly and negatively related with a wide range of risk factors and mental health outcomes especially depression before, during and after pregnancy. Conclusions ALPHA proved to be a valid, feasible and reliable instrument to Primary Health Care (PHC) that can be used as a total sum score. We could not prove the association between psychosocial risk factors and MFA, neither between MFA and EA, or between psychosocial risk and EA. Depression and SOC seems to have a clear and opposite relevance on this process. Pregnancy can be considered as a maturational process and an opportunity to change, where adaptation processes occur, buffering risk, decreasing depression and increasing SOC. Further research is necessary to better understand interactions between variables and also to clarify a better operationalization of MFA. We recommend the use of ALPHA, SOC and EDPS in early pregnancy as a way of identifying more vulnerable women that will require additional interventions and support in order to decrease risk. At political level we recommend the reinforcement of Immigrant integration and the increment of education in women. We recommend more focus in health care and public health in mental health condition and psychosocial risk of specific groups at high risk. In PHC special attention should be paid to pregnant women who are single or divorced, very young, low educated and to immigrant mothers. This study provides the basis for an intervention programme for this population, that aims to reduce broad spectrum risk factors and to promote Mental Health in women who become pregnant. Health and mental health policies should facilitate the implementation of the suggested measures.

A DSL for querying building data streams of energy, eeather and occupation data

The superfluous consumption of energy is faced by the modern society as a Socio-Economical and Environmental problem of the present days. This situation is worsening given that it is becoming clear that the tendency is to increase energy price every year. It is also noticeable that people, not necessarily proficient in technology, are not able to know where savings can be achieved, due to the absence of accessible awareness mechanisms. One of the home user concerns is to balance the need of reducing energy consumption, while producing the same activity with all the comfort and work efficiency. The common techniques to reduce the consumption are to use a less wasteful equipment, altering the equipment program to a more economical one or disconnecting appliances that are not necessary at the moment. However, there is no direct feedback from this performed actions, which leads to the situation where the user is not aware of the influence that these techniques have in the electrical bill. With the intension to give some control over the home consumption, Energy Management Systems (EMS) were developed. These systems allow the access to the consumption information and help understanding the energy waste. However, some studies have proven that these systems have a clear mismatch between the information that is presented and the one the user finds useful for his daily life, leading to demotivation of use. In order to create a solution more oriented towards the user’s demands, a specially tailored language (DSL) was implemented. This solution allows the user to acquire the information he considers useful, through the construction of questions about his energy consumption. The development of this language, following the Model Driven Development (MDD) approach, took into consideration the ideas of facility managers and home users in the phases of design and validation. These opinions were gathered through meetings with experts and a survey, which was conducted to the purpose of collecting statistics about what home users want to know.