Influência de filtros de ruído dinâmico na perceção das cores utilizando um novo teste de visão das cores

Dissertação de mestrado em Optometria Avançada

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

The economic crisis in Portugal and children’s rights to non-discrimination

The consequences that arose from the ‘global economy’ have been significant in Portuguese children’s lives and we believe it is fundamental to reflect on the ongoing structuring of childhood through this global culture/ideology and the concrete implications that they have. It is also important to understand how childhood is constructed and experienced, as well as to consider the impacts of political economic conditions on children’s lives and in childhood in general, taking into account the effects brought on by public policies. The aim of this paper is to reflect on the ways through which the economic crisis affecting the general Portuguese population has impacted children in particular and promoted discrimination and a lack of opportunities in childhood. We will focus on two dimensions: first, on general data about the ongoing policies that have been reducing social rights, increasing poverty rates and threatening basic rights such as educational and health rights, to show their impact on children´s lives. Second, we will discuss some data collected with children throughout different research projects in order to characterize the meanings and impacts of the crisis in their lives from their points of view

Discrimination of bacteriophage infected cells using locked nucleic acid fluorescent in situ hybridization (LNA-FISH)

Bacteriophage-host interaction studies in biofilm structures are still challenging due to the technical limitations of traditional methods. The aim of this study was to provide a direct fluorescence in situ hybridization (FISH) method based on locked nucleic acid (LNA) probes, which targets the phage replication phase, allowing the study of population dynamics during infection. Bacteriophages specific for two biofilm-forming bacteria, Pseudomonas aeruginosa and Acinetobacter, were selected. Four LNA probes were designed and optimized for phage-specific detection and for bacterial counterstaining. To validate the method, LNA-FISH counts were compared with the traditional plaque forming unit (PFU) technique. To visualize the progression of phage infection within a biofilm, colony-biofilms were formed and infected with bacteriophages. A good correlation (r=0.707) was observed between LNA-FISH and PFU techniques. In biofilm structures, LNA-FISH provided a good discrimination of the infected cells and also allowed the assessment of the spatial distribution of infected and non-infected populations.

Behavior-based price discrimination in a multi-dimensional preferences market

NIPE WP 04/ 2016

As cores de Braga: levantamento cromático da rua do Souto e da rua D. Diogo de Sousa

Dissertação de mestrado integrado em Arquitectura (área de especialização em Cultura Arquitectónica)