Exploring the role of O-Mannosylation in the modulation of E-Cadherin function in Gastric Cancer cell line models

Dissertação de mestrado em Bioquímica Aplicada – Biomedicina

Sucesso escolar e percursos vocacionais na adolescência: variáveis pessoais e contextuais

Tese de Doutoramento Ciências da Educação (Especialidade em Psicologia da Educação)

Contributos dos ambientes digitais online para a aprendizagem em contexto de atividades de apoio extraescolar

Dissertação de mestrado em Ciências da Educação (área de especialização em Tecnologia Educativa)

Participação de fisioterapeutas em equipes multidisciplinares que atuam junto a alunos com necessidades educativas especiais: um estudo quantitativo em escolas de ensino fundamental da rede pública de Manaus

Dissertação de mestrado em Educação Especial (área de especialização em Dificuldades de Aprendizagem Específicas)

Formação de professores: uma prática pedagógica frente aos desafios das necessidades educativas especiais: um estudo de caso numa IES Particular em Manaus-Am

Dissertação de mestrado em Educação Especial (área de especialização em Dificuldades de Aprendizagem Específicas)

Psychosocial adjustment and physical health in children of divorce

Objective: To review the literature on the effects of parental divorce over the psychological maladjustment and physical health problems in children of divorced parents, thus contributing to the integration of existing scientific knowledge based on the biopsychosocial model of the impact of divorce on children’s physical health as proposed by Troxel and Matthews (2004). Sources: Review of the literature using MEDLINE and PsycInfo (1980-2007) databases, selecting the most representative articles on the subject. Special attention was paid to contributions by internationally renowned investigators on the subject. Summary of the findings: Divorce may be responsible for a decline of physical and psychological health in children. The developmental maladjustment of children is not triggered by divorce itself, but rather by other risk factors associated with it, such as interparental conflict, parental psychopathology, decline in socio-economic level, inconsistency in parenting styles, a parallel and conflicting co-parenting relationship between parents and low levels of social support. Such risk factors trigger maladjusted developmental pathways, marked by psychopathological symptoms, poor academic performance, worst levels of physical health, risk behavior, exacerbated psychophysiological responses to stress and weakening of the immune system. Conclusions: Clear links were observed between experiencing parental divorce and facing problems of physical and psychological maladjustment in children. Divorce is a stressor that should be considered by health professionals as potentially responsible for maladjusted neuropsychobiological responses and for decline in children’s physical health.

Pervasive decision support to predict football corners and goals by means of data mining

Football is considered nowadays one of the most popular sports. In the betting world, it has acquired an outstanding position, which moves millions of euros during the period of a single football match. The lack of profitability of football betting users has been stressed as a problem. This lack gave origin to this research proposal, which it is going to analyse the possibility of existing a way to support the users to increase their profits on their bets. Data mining models were induced with the purpose of supporting the gamblers to increase their profits in the medium/long term. Being conscience that the models can fail, the results achieved by four of the seven targets in the models are encouraging and suggest that the system can help to increase the profits. All defined targets have two possible classes to predict, for example, if there are more or less than 7.5 corners in a single game. The data mining models of the targets, more or less than 7.5 corners, 8.5 corners, 1.5 goals and 3.5 goals achieved the pre-defined thresholds. The models were implemented in a prototype, which it is a pervasive decision support system. This system was developed with the purpose to be an interface for any user, both for an expert user as to a user who has no knowledge in football games.

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.