RAISING INTERCULTURAL AWARENESS AT PRIMARY LEVEL THROUGH STORYTELLING WITHIN A CLIL APPROACH

Trabalho de Projecto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Ensino de Inglês

THE U.S. and European M&A cycles: A Markov switching and state space approach

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Voting and Peer Effects: Experimental Evidence from Mozambique*

Voter education campaigns often aim to increase voter particpation and political accountability. We follow randomized interventions implemented nationwide during the 2009 Mozambican elections using a free newspaper, leaflets, and text messaging. We investigate whether treatment effects were transmitted through social networks (kinship and chatting) and geographical proximity. For individuals personally targeted by the campaign, we estimate the reinforcement effect of proximity to other targeted individuals. For untargeted individuals, we estimate the diffusion of the campaign depending on a proximity to targeted individuals. We find evidence for both effects, similar across the different treatments and across the different connectedness measures. We observe that the treatments worked through the networks by raising the levels of information and interest about the election, in line with the average treatment effects of voter education on voter participation. We interpret this result as a free riding effect, likely to occur for costly actions

HOMO-raising strategies in aminocatalysis, from Enamine to Tetraenamine

Dissertação para obtenção do Grau de Mestre em Bioorgânica

Service-oriented infrastructure to support the control, monitoring and management of a shop floor system

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Land cover mapping analysis and urban growth modeling using remote sensing techniques

The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively.