Modelling tyre-road noise with data mining techniques

The research aimed to establish tyre-road noise models by using a Data Mining approach that allowed to build a predictive model and assess the importance of the tested input variables. The data modelling took into account three learning algorithms and three metrics to define the best predictive model. The variables tested included basic properties of pavement surfaces, macrotexture, megatexture, and uneven- ness and, for the first time, damping. Also, the importance of those variables was measured by using a sensitivity analysis procedure. Two types of models were set: one with basic variables and another with complex variables, such as megatexture and damping, all as a function of vehicles speed. More detailed models were additionally set by the speed level. As a result, several models with very good tyre-road noise predictive capacity were achieved. The most relevant variables were Speed, Temperature, Aggregate size, Mean Profile Depth, and Damping, which had the highest importance, even though influenced by speed. Megatexture and IRI had the lowest importance. The applicability of the models developed in this work is relevant for trucks tyre-noise prediction, represented by the AVON V4 test tyre, at the early stage of road pavements use. Therefore, the obtained models are highly useful for the design of pavements and for noise prediction by road authorities and contractors.

Ex situ collection of Limonium spp.: cytogenetic and reproductive characterization for the conservation of rare species

Dissertação mestrado em Biologia Molecular, Biotecnologia e Bioempreendedorismo em Plantas

Poly lactic acid based biodegradable stents and functionalization techniques: brief review

Commercial stents, especially metallic ones, present several disadvantages, and this gives rise to the necessity of producing or coating stents with different materials, like natural polymers, in order to improve their biocompatibility and minimize the disadvantages of metallic ones. This review paper discusses some applications of natural-based polymers in stents, namely polylactic acid (PLA) for stent development and chitosan for biocompatible coatings of stents . Furthermore, some effective stent functionalization techniques will be discussed, namely Layer by Layer (LBL) technique.

A 3D computer assisted Orthopedic Surgery Planning approach based on planar radiography

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)

Dos efeitos da Procriação Medicamente Assistida no Direito Sucessório

Dissertação de mestrado em Direito das Crianças, Família e Sucessões

Couple's willingness to donate embryos for research: a longitudinal study

Introduction. Decision-making on embryo disposition is a source of distress and is subject to change over time. This paper analyses the willingness of couples undergoing in vitro fertilization to donate cryopreserved embryos for research from 15 days after embryo transfer to 12 months later, taking into account the influence of psychosocial, demographic, and reproductive factors. Materials and methods. Prospective longitudinal study, with 74 heterosexual couples undergoing in vitro fertilization in a public fertility centre in Portugal, recruited between 2011 and 2012. Participants were evaluated twice: 15 days after embryo transfer and 12 months later. Results. A significant decrease in patients’ willingness to donate embryos for research over time was observed [86.5% to 73.6%; relative risk (RR) = 0.85; 95% CI 0.76–0.95]. A higher education level (>12 years) [adjusted RR (RRadj) = 0.79; 95% CI 0.64–0.96], considering research on human embryos to be important (vs. very important) (RRadj = 0.59; 95% CI 0.39–0.85) and practicing a religion less than once a month (vs. at least once a month) (RRadj = 0.73; 95% CI 0.53–1.00) seemed associated with unwillingness to donate embryos for research over time. Change towards non-donation happened mainly among couples who first considered that it was better to donate than wasting the embryos. Change towards donation occurred mostly among those stating that their priority at time 1 was to have a baby and who became pregnant in the meantime. Conclusions. Quality of care guided by patients’ characteristics, values, preferences, and needs calls for considering the factors and reasons underlying couples’ willingness to donate embryos for research over time as a topic in psychosocial guidelines for infertility and medically assisted reproductive care.

Factors associated with the donation and non-donation of embryos for research: a systematic review

Background: Systematic knowledge on the factors that influence the decisions of IVF users regarding embryo donation for research is a core need for patient-centred policies and ethics in clinical practice. However, no systematic review has been provided on the motivations of patients who must decide embryo disposition. This paper fills this gap, presenting a systematic review of quantitative and qualitative studies, which synthesizes the current body of knowledge on the factors and reasons associated with IVF patients’ decisions to donate or not to donate embryos for research. Methods: A systematic search of studies indexed in PubMed, ISIWoK and PsycINFO, published before November 2013, was conducted. Only empirical, peer-reviewed, full-length, original studies reporting data on factors and reasons associated with the decision concerning donation or non-donation of embryos for research were included. Eligibility and data extraction were performed by two independent researchers and disagreements were resolved by discussion or a third reviewer, if required. The main quantitative findings were extracted and synthesized and qualitative data were assessed by thematic content analysis. Results: A total of 39 studies met the inclusion criteria and were included in the review. More than half of the studies (n ¼ 21) used a quantitative methodology, and the remaining were qualitative (n ¼ 15) or mixed-methods (n ¼ 3) studies. The studies were derived mainly from European countries (n ¼ 18) and the USA(n ¼ 11). The proportion of IVF users who donated embryos for research varied from 7% in a study in France to 73% in a Swiss study. Those who donate embryos for research reported feelings of reciprocity towards science and medicine, positive views of research and high levels of trust in the medical system. They described their decision as better than the destruction of embryos and as an opportunity to help others or to improve health and IVF treatments. The perception of risks, the lack of information concerning research projects and the medical system and the conceptualization of embryos in terms of personhood were the most relevant motives for not donating embryos for research. Results relating to the influence of sociodemographic characteristics and reproductive and gynaecological history were mostly inconclusive. Conclusions: Three iterative and dynamic dimensions of the IVF patients’ decision to donate or not to donate embryos for research emerged from this review: the hierarquization of the possible options regarding embryo disposition, according to the moral, social and instrumental status attributed to embryos; patients’ understanding of expectations and risks of the research on human embryos; and patients’ experiences of information exchange and levels of trust in the medical-scientific institutions.

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.