Applying complex network theory to the understanding of high-aspect-ratio carbon-filled composites

This work demonstrates that the theoretical framework of complex networks typically used to study systems such as social networks or the World Wide Web can be also applied to material science, allowing deeper understanding of fundamental physical relationships. In particular, through the application of the network theory to carbon nanotubes or vapour-grown carbon nanofiber composites, by mapping fillers to vertices and edges to the gap between fillers, the percolation threshold has been predicted and a formula that relates the composite conductance to the network disorder has been obtained. The theoretical arguments are validated by experimental results from the literature.

The influence of matrix mediated hopping conductivity, filler concentration, aspect ratio and orientation on the electrical response of carbon nanotube/polymer nanocomposites

A model to simulate the conductivity of carbon nanotube/polymer nanocomposites is presented. The proposed model is based on hopping between the fillers. A parameter related to the influence of the matrix in the overall composite conductivity is defined. It is demonstrated that increasing the aspect ratio of the fillers will increase the conductivity. Finally, it is demonstrated that the alignment of the filler rods parallel to the measurement direction results in higher conductivity values, in agreement with results from recent experimental work.

Analysis of the return on preventive measures in musculoskeletal disorders through the benefitecost ratio: A case study in a hospital

Work-related musculoskeletal disorders (WMSDs) are among the most costly health problems that society is facing today. Prevention involves investments and it is important for organizations to make a cost ebenefit analysis of ergonomic projects. Return on prevention is a recent concern in the domain of occupational safety and health (OSH). There are many studies concerning the return on the prevention of WMSDs, in terms of the benefits for the organization in which the preventive measures are implemented. However, it is also important to perform an analysis of the impact of each measure on society (externalities). A model to perform a financial and economic costebenefit analysis related to OSH projects was developed and it was applied in the case of the prevention of WMSDs in a Portuguese hospital. An analysis of the accidents and corresponding costs has been made in six of the services of the hospital. Financial and an economic costebenefit analysis have been made and the benefitecost ratio (B/C) has been calculated. While the B/C financial ratio, considering only the benefits to the hospital, is around 2, the economic B/C ratio, taking into account all the external benefits that have been quantified, is higher than 14. Relevance to industry: Both the economic and the financial B/C ratio are important support tools for decision makers in public and private organizations, helping them to define which preventive measures should be implemented, taking into account the costs involved and the resulting quantified benefits, for the organization, for the workers and for the society.

Effects and determinants of household debt in Portugal

As the amount of debt has gradually increased, particularly in recent years, Portugal is currently one of the European countries exhibiting one of the highest levels of overall indebtedness, including in both sovereign and private sectors. Indeed, this condition is the outcome of increasing levels of debt assumed not only by the government, but also by companies and families, being the later mostly due to mortgage loans and due charges. This paper focuses on the study of borrowing by Portuguese households. The research has been made in respect to the notion of debt, the consequences of recent developments in debt, among other factors. In order to analyse the factors that are most associated with debt, a study was developed using two multiple regression models, one using a longer time series and another shorter, evaluating the effect of several variables, such as consumption, savings, unemployment, inflation and interest rates, in order to check whether they could be associated with a higher level of debt.