Avaliação da dose absorvida na tiróide, em cintigrafias com 123I e Na99mTcO4 utilizando modelos biocinéticos e métodos de Monte Carlo

Mestrado em Radiações Aplicadas às Tecnologias da Saúde. Área de especialização: Protecção contra Radiações

Characterization of earth-based mortars for rammed earth repair

All over the world, many earth buildings are deteriorating due to lack of maintenance and repair. Repairs on rammed earth walls are mainly done with mortars, by rendering application; however, often the repair is inadequate, resorting to the use of incompatible materials, including cement-based mortars. It has been observed that such interventions, in walls that until that day only had presented natural ageing issues, created new problems, much more dangerous for the building than the previous ones, causing serious deficiencies in this type of construction. One of the problems is that the detachment of the new cement-based mortar rendering only occurs after some time but, until that occurrence, degradations develop in the wall itself. When the render detaches, instead of needing only a new render, the surface has to be repaired in depth, with a repair mortar. Consequently, it has been stablished that the renders, and particularly repair mortars, should have physical, mechanical and chemical properties similar to those of the rammed earth walls. This article intends to contribute to a better knowledge of earth-based mortars used to repair the surface of rammed earth walls. The studied mortars are based on four types of earth: three of them were collected from non-deteriorated parts of walls of unstabilized rammed earth buildings located in Alentejo region, south of Portugal; the fourth is a commercial earth, consisting mainly of clay. Other components were also used, particularly: sand to control shrinkage; binders stabilizers such as dry hydrated air-lime, natural hydraulic lime, Portland cement and natural cement; as well as natural vegetal fibers (hemp fibers). The experimental analysis of the mortars in the fresh state consisted in determining the consistency by flow table and the bulk density. In the hardened state, the tests made it possible to evaluate the following properties: linear and volumetric shrinkage; capillary water absorption; drying capacity; dynamic modulus of elasticity; flexural and compressive strength.

Processos de melhoria social: a requalificação do Bairro Social de Santa Tecla

Dissertação de mestrado integrado em Arquitectura

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

A systematic study of the structural and magnetic properties of Mn-, Co-, and Ni-Doped Colloidal Fe3O4 nanoparticles

A series of colloidal MxFe3-xO4 (M = Mn, Co, Ni; x = 0–1) nanoparticles with diameters ranging from 6.8 to 11.6 nm was synthesized by hydrothermal reaction in aqueous medium at low temperature (200 °C). Energy-dispersive X-ray microa-nalysis and inductively coupled plasma spectrometry confirms that the actual elemental compositions agree well with the nominal ones. The structural properties of obtained nanoparticles were investigated by using powder X-ray diffraction, Raman scattering, Mössbauer spectroscopy, and electron microscopy. The results demonstrate that our synthesis technique leads to the formation of chemically uniform single-phase solid solution nanoparticles with cubic spinel structure, confirming the intrinsic doping. Magnetic studies showed that, in comparison to Fe3O4, the saturation magnetization of MxFe3-xO4 (M = Mn, Ni) decreases with increasing dopant concentration, while Co-doped samples showed similar saturation magnetizations. On other hand, whereas Mn- and Ni-doped nanoparticles exhibits superparamagnetic behavior at room temperature, ferromagnetism emerges for CoxFe3-xO4 nanoparticles, which can be tuned by the level of Co doping.

Tapping the wealth of microbial data in high-throughput metabolic model reconstruction

Genome-scale metabolic models are valuable tools in the metabolic engineering process, based on the ability of these models to integrate diverse sources of data to produce global predictions of organism behavior. At the most basic level, these models require only a genome sequence to construct, and once built, they may be used to predict essential genes, culture conditions, pathway utilization, and the modifications required to enhance a desired organism behavior. In this chapter, we address two key challenges associated with the reconstruction of metabolic models: (a) leveraging existing knowledge of microbiology, biochemistry, and available omics data to produce the best possible model; and (b) applying available tools and data to automate the reconstruction process. We consider these challenges as we progress through the model reconstruction process, beginning with genome assembly, and culminating in the integration of constraints to capture the impact of transcriptional regulation. We divide the reconstruction process into ten distinct steps: (1) genome assembly from sequenced reads; (2) automated structural and functional annotation; (3) phylogenetic tree-based curation of genome annotations; (4) assembly and standardization of biochemistry database; (5) genome-scale metabolic reconstruction; (6) generation of core metabolic model; (7) generation of biomass composition reaction; (8) completion of draft metabolic model; (9) curation of metabolic model; and (10) integration of regulatory constraints. Each of these ten steps is documented in detail.

Distributed Repositories of Medieval Calendars and Crowd-Sourcing of Transcription

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

HiberActive: Pro-Active Archiving of Web References from Scholarly Articles

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014