Masonry infill walls under blast loading using confined underwater blast wave generators (WBWG)

The vulnerability of the masonry envelop under blast loading is considered critical due to the risk of loss of lives. The behaviour of masonry infill walls subjected to dynamic out-of-plane loading was experimentally investigated in this work. Using confined underwater blast wave generators (WBWG), applying the extremely high rate conversion of the explosive detonation energy into the kinetic energy of a thick water confinement, allowed a surface area distribution avoiding also the generation of high velocity fragments and reducing atmospheric sound wave. In the present study, water plastic containers, having in its centre a detonator inside a cylindrical explosive charge, were used in unreinforced masonry infills panels with 1.7m by 3.5m. Besides the usage of pressure and displacement transducers, pictures with high-speed video cameras were recorded to enable processing of the deflections and identification of failure modes. Additional numerical studies were performed in both unreinforced and reinforced walls. Bed joint reinforcement and grid reinforcement were used to strengthen the infill walls, and the results are presented and compared, allowing to obtain pressure-impulse diagrams for design of masonry infill walls.

Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach

Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.

Análise e melhoria da produtividade numa empresa do sector de componentes de automóveis

Dissertação de mestrado integrado em Engenharia e Gestão Industrial

Marine origin polysaccharides in drug delivery systems

Oceans are a vast source of natural substances. In them, we find various compounds with wide biotechnological and biomedical applicabilities. The exploitation of the sea as a renewable source of biocompounds can have a positive impact on the development of new systems and devices for biomedical applications. Marine polysaccharides are among the most abundant materials in the seas, which contributes to a decrease of the extraction costs, besides their solubility behavior in aqueous solvents and extraction media, and their interaction with other biocompounds. Polysaccharides such as alginate, carrageenan and fucoidan can be extracted from algae, whereas chitosan and hyaluronan can be obtained from animal sources. Most marine polysaccharides have important biological properties such as biocompatibility, biodegradability, and anti-inflammatory activity, as well as adhesive and antimicrobial actions. Moreover, they can be modified in order to allow processing them into various shapes and sizes and may exhibit response dependence to external stimuli, such as pH and temperature. Due to these properties, these biomaterials have been studied as raw material for the construction of carrier devices for drugs, including particles, capsules and hydrogels. The devices are designed to achieve a controlled release of therapeutic agents in an attempt to fight against serious diseases, and to be used in advanced therapies, such as gene delivery or regenerative medicine.

Antibiofilm strategies in the food industry

Biofilms in food processing plants represent not only a problem to human health but also cause economic losses by technical failure in several systems. In fact, many foodborne outbreaks have been found to be associated with biofilms. Biofilms may be prevented by regular cleaning and disinfection, but this does not completely prevent biofilm formation. Besides, due to their diversity and to the development of specialized phenotypes, it is well known that biofilms are more resistant to cleaning and disinfection than planktonic microorganisms. In recent years, a considerable effort has been made in the prevention of microbial adhesion and biofilm formation on food processing surfaces and novel technologies have been introduced. In this context, this chapter discusses the main conventional and emergent strategies that have been employed to prevent bacterial adhesion to food processing surfaces and thus to efficiently maintain good hygiene throughout the food industries.

Prospecção de ocorrências filonianas do tipo LCT nas formações metassedimentares entre Boticas e Montalegre (N de Portugal)

Dissertação de mestrado em Geologia (área de especialização em Valorização de Recursos Geológicos)

Nanocomposites: the contribution of multiscale modelling to improve the dispersion levels

Tese de Doutoramento em Ciência e Engenharia de Polímeros e Compósitos