Using mouse dynamics to assess stress during online exams

"Lecture notes in computer science series", ISSN 0302-9743, vol. 9121

Videovigilância: privacidade e segurança: análise especial da situação do trabalhador

Dissertação de mestrado em Direitos Humanos

Velhas e novas drogas: impactos da toxicodependência: estudo de caso na cidade de Braga

Dissertação de mestrado em Sociologia (área de especialização em Organizações e Trabalho)

Critical events in mechanically ventilated patients

Mechanical Ventilation is an artificial way to help a Patient to breathe. This procedure is used to support patients with respiratory diseases however in many cases it can provoke lung damages, Acute Respiratory Diseases or organ failure. With the goal to early detect possible patient breath problems a set of limit values was defined to some variables monitored by the ventilator (Average Ventilation Pressure, Compliance Dynamic, Flow, Peak, Plateau and Support Pressure, Positive end-expiratory pressure, Respiratory Rate) in order to create critical events. A critical event is verified when a patient has a value higher or lower than the normal range defined for a certain period of time. The values were defined after elaborate a literature review and meeting with physicians specialized in the area. This work uses data streaming and intelligent agents to process the values collected in real-time and classify them as critical or not. Real data provided by an Intensive Care Unit were used to design and test the solution. In this study it was possible to understand the importance of introduce critical events for Mechanically Ventilated Patients. In some cases a value is considered critical (can trigger an alarm) however it is a single event (instantaneous) and it has not a clinical significance for the patient. The introduction of critical events which crosses a range of values and a pre-defined duration contributes to improve the decision-making process by decreasing the number of false positives and having a better comprehension of the patient condition.

Pervasive patient timeline for intensive care units

This research work explores a new way of presenting and representing information about patients in critical care, which is the use of a timeline to display information. This is accomplished with the development of an interactive Pervasive Patient Timeline able to give to the intensivists an access in real-time to an environment containing patients clinical information from the moment in which the patients are admitted in the Intensive Care Unit (ICU) until their discharge This solution allows the intensivists to analyse data regarding vital signs, medication, exams, data mining predictions, among others. Due to the pervasive features, intensivists can have access to the timeline anywhere and anytime, allowing them to make decisions when they need to be made. This platform is patient-centred and is prepared to support the decision process allowing the intensivists to provide better care to patients due the inclusion of clinical forecasts.

Optimization techniques to detect early ventilation extubation in intensive care units

The decision support models in intensive care units are developed to support medical staff in their decision making process. However, the optimization of these models is particularly difficult to apply due to dynamic, complex and multidisciplinary nature. Thus, there is a constant research and development of new algorithms capable of extracting knowledge from large volumes of data, in order to obtain better predictive results than the current algorithms. To test the optimization techniques a case study with real data provided by INTCare project was explored. This data is concerning to extubation cases. In this dataset, several models like Evolutionary Fuzzy Rule Learning, Lazy Learning, Decision Trees and many others were analysed in order to detect early extubation. The hydrids Decision Trees Genetic Algorithm, Supervised Classifier System and KNNAdaptive obtained the most accurate rate 93.2%, 93.1%, 92.97% respectively, thus showing their feasibility to work in a real environment.

Real-Time models to predict the use of vasopressors in monitored patients

The needs of reducing human error has been growing in every field of study, and medicine is one of those. Through the implementation of technologies is possible to help in the decision making process of clinics, therefore to reduce the difficulties that are typically faced. This study focuses on easing some of those difficulties by presenting real-time data mining models capable of predicting if a monitored patient, typically admitted in intensive care, will need to take vasopressors. Data Mining models were induced using clinical variables such as vital signs, laboratory analysis, among others. The best model presented a sensitivity of 94.94%. With this model it is possible reducing the misuse of vasopressors acting as prevention. At same time it is offered a better care to patients by anticipating their treatment with vasopressors.

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%.

Conceptualização de um projecto urbano

Dissertação apresentada na Universidade de Lisboa - Faculdade de Arquitetura, para obtenção do Grau de Mestre em Arquitetura.

Cidade de Miradouro

Dissertação apresentada na Universidade de Lisboa - Faculdade de Arquitetura, para obtenção do Grau de Mestre em Arquitetura.

Assessment of Myocardial Infarction by Cardiac Magnetic Resonance Imaging and Long-Term Mortality

Background: Cardiac magnetic resonance imaging provides detailed anatomical information on infarction. However, few studies have investigated the association of these data with mortality after acute myocardial infarction. Objective: To study the association between data regarding infarct size and anatomy, as obtained from cardiac magnetic resonance imaging after acute myocardial infarction, and long-term mortality. Methods: A total of 1959 reports of “infarct size” were identified in 7119 cardiac magnetic resonance imaging studies, of which 420 had clinical and laboratory confirmation of previous myocardial infarction. The variables studied were the classic risk factors – left ventricular ejection fraction, categorized ventricular function, and location of acute myocardial infarction. Infarct size and acute myocardial infarction extent and transmurality were analyzed alone and together, using the variable named “MET-AMI”. The statistical analysis was carried out using the elastic net regularization, with the Cox model and survival trees. Results: The mean age was 62.3 ± 12 years, and 77.3% were males. During the mean follow-up of 6.4 ± 2.9 years, there were 76 deaths (18.1%). Serum creatinine, diabetes mellitus and previous myocardial infarction were independently associated with mortality. Age was the main explanatory factor. The cardiac magnetic resonance imaging variables independently associated with mortality were transmurality of acute myocardial infarction (p = 0.047), ventricular dysfunction (p = 0.0005) and infarcted size (p = 0.0005); the latter was the main explanatory variable for ischemic heart disease death. The MET-AMI variable was the most strongly associated with risk of ischemic heart disease death (HR: 16.04; 95%CI: 2.64-97.5; p = 0.003). Conclusion: The anatomical data of infarction, obtained from cardiac magnetic resonance imaging after acute myocardial infarction, were independently associated with long-term mortality, especially for ischemic heart disease death.

Presença de Panstrongylus megistus infectado por Schizotrypanum no Rio de Janeiro, D. F

É referido o encontro de barbeiros (Panstrongylus megistus) adultos em residências do Distrito Federal, nos bairros de Santa Teresa (Rua Almirante Alexandrino) e de Botafogo (Travessa João Afonso). Um exemplar capturado em Santa Teresa estava infectado por flagelados, critidias e tripanosomas metacíclicos, fato pela primeira vez assinalado na Capital da República. Dejeções no inseto infectado foram inoculadas em camondongos brancos, determinando apenas infecções sanguíneas inaparentes, reveladas pelo xenodiagnóstico. Entretanto, no exsudato peritoneal dos animais foram encontrados a fresco tripanosomas com caracters de Schizotrypanum. Os transmissores da doença de chagas até agora referidos no Distrito Federal são: Panstrongylus megistus, Panstrongylus geniculatus, Triatoma vitticeps, Triatoma oswaldoi e Triatoma rubrofasciata.

El Giravolt de la Família Robafaves

Treball de recerca realitzat per un alumne d'ensenyament secundari i guardonat amb un Premi CIRIT per fomentar l'esperit cientí­fic del Jovent l'any 2009. 'El Giravolt de la Família Robafaves' és un treball de recerca que engloba tota la història del fet geganter a Mataró des dels seus orígens fins a l'actualitat. Es tracta d'una activitat amb una dimensió cultural, folklòrica i històrica que ha servit per donar respostes a molts dels interrogants promulgats abans de dur a terme aquest projecte. Aquesta família de Gegants ha estat víctima de molts dels entrebancs vigents al llarg de la història així com guerres, revoltes, dictadures, etc. De manera que s'ha pogut comprovar com la política interior i exterior ha afectat a la Família Robafaves d'una manera directa. S'ha fet una investigació a través de les revistes publicades durant la transició democràtica. També cal dir que, s'ha tingut el recolzament d'entrevistes fetes a persones puntals en la història dels Gegants com ara geganters, Caps de Colla, la primera gegantera de la Família Robafaves, etc. Per poder corroborar la base teòrica i documental d'aquest treball s'ha fet un estudi estadístic de la significació social de la Festa Major de Mataró per poder valorar en quina situació es troba actualment. Així doncs, s'ha pogut valorar la influència i importància que tenen els Gegants per Mataró.

Relíquies de sants : vestigis del passat, símbols del present

Descripció de les manifestacions devotes a les relíquies dins les festes majors de Ripoll, Camprodon, Vic i la Festa del Pi de Centelles en les quals es veneren les relíquies de sant Eudald, sant Patllari, sant Miquel dels Sants i santa Coloma, respectivament.

Hospitalization due to norovirus and genotypes of rotavirus in pediatric patients, state of Espírito Santo

Viruses are the leading cause for hospitalization due to gastroenteritis worldwide. Group A rotaviruses (RV) are the most prevalent and are assorted in glycoproteins (G) and protease sensitive (P) dual genotypes based on polymorphic genes that encode the external VP7 and VP4 capsid proteins, respectively. Noroviruses (NoV) have increasingly answered by sporadic gastroenteritis. This study aimed to determine the prevalence of NoV and RV in 68 hospitalized children, between July 2004 and November 2006, at a pediatric hospital in Vitória city, state of Espírito Santo, Southeastern Brazil. Nucleic acid was extracted from fecal suspension following the guanidine-silica procedure. Reverse transcriptase-polymerase chain reaction (RT-PCR) and polyacrylamide gel electrophoresis were employed for NoV and RV detection, respectively. RV genotyping was accomplished using RT-PCR followed by heminested multiplex PCR with specific primers for the most prevalent types of G and P. Fecal samples were positive for NoV and RV in 39.7% (27/68) and 20.5% (14/68), respectively and together were responsible for 60% (41/68) of the cases. RV genotypes were: 50% G9P[8], 28.7% G2P[4], 7.1% G1P[8], G2P[8] and G?P[8]. Vomit was a prominent manifestation observed in 92% and 85% of the NoV and RV cases, respectively. The median hospitalization was 5 and 5.5 days for the patients infected with NoV and RV, respectively. The data showed that NoV prevailed over RV and it also corroborated the emergence of RV G9 genotype followed by G2P[4], reinforcing the need for RV genotype surveillance.