Upgrade of an industrial building: BIM model of the as-built situation and evaluation of modifications

Dissertação de mestrado integrado in Civil Engineering

School governance and academic excellence: the representations of distinguished students in an annual award of excellence

Within a research project on «academic excellence in the state school», this paper is a contribution to the sociological reflection on the cultural and organisational characteristics of the school and its relationship with the academic success of students. The data we present stem from a case study underway at a secondary school in the north of Portugal, referring to the universe of students that since 2003 have distinguished themselves for achieving grades equal to or greater than 18 (on a scale of 0 to 20) and have thus been included in the school’s Framework of Excellence. From a contextual approach to this educational practice, we focused on the cultural characteristics of the school/subject as analytical support for the study of school and non-school dimensions in their mutual connections. To this end, we used the information from document analysis and data collected from a questionnaire survey administered to more than two-thirds of the students included in the above-mentioned Framework of Excellence. Subsequently, we will use the data from this survey to understand the extent to which academic excellence is perceived as an indivisible social construction of the school’s political and organisational matrix, particularly in terms of the educational and teaching guidelines adopted by the management body. We will conclude by questioning the meaning of the school’s management policies regarding the emphasis on educational outcomes, with particular focus on the representations of excellent students in the processes of school leadership, teaching organisation, school merit and justice.

Development of computational and experimental methods for biomass composition and evaluation of its impact in genome-scale models prediction

The use of genome-scale metabolic models has been rapidly increasing in fields such as metabolic engineering. An important part of a metabolic model is the biomass equation since this reaction will ultimately determine the predictive capacity of the model in terms of essentiality and flux distributions. Thus, in order to obtain a reliable metabolic model the biomass precursors and their coefficients must be as precise as possible. Ideally, determination of the biomass composition would be performed experimentally, but when no experimental data are available this is established by approximation to closely related organisms. Computational methods however, can extract some information from the genome such as amino acid and nucleotide compositions. The main objectives of this study were to compare the biomass composition of several organisms and to evaluate how biomass precursor coefficients affected the predictability of several genome-scale metabolic models by comparing predictions with experimental data in literature. For that, the biomass macromolecular composition was experimentally determined and the amino acid composition was both experimentally and computationally estimated for several organisms. Sensitivity analysis studies were also performed with the Escherichia coli iAF1260 metabolic model concerning specific growth rates and flux distributions. The results obtained suggest that the macromolecular composition is conserved among related organisms. Contrasting, experimental data for amino acid composition seem to have no similarities for related organisms. It was also observed that the impact of macromolecular composition on specific growth rates and flux distributions is larger than the impact of amino acid composition, even when data from closely related organisms are used.