X-ray crystal structure and EPR spectra of "arsenite-inhibited" Desulfovibriogigas aldehyde dehydrogenase: a member of the xanthine oxidase family

J. Am. Chem. Soc., 2004, 126 (28), pp 8614–8615 DOI: 10.1021/ja0490222

Learning networks and moodle use in online courses: a social network analysis study

Dissertação para obtenção do Grau de Doutor em Ciências da Educação Especialidade em Tecnologias, Redes e Multimédia na Educação e Formação

A framework for efficient model transformations

The reported productivity gains while using models and model transformations to develop entire systems, after almost a decade of experience applying model-driven approaches for system development, are already undeniable benefits of this approach. However, the slowness of higher-level, rule based model transformation languages hinders the applicability of this approach to industrial scales. Lower-level, and efficient, languages can be used but productivity and easy maintenance seize to exist. The abstraction penalty problem is not new, it also exists for high-level, object oriented languages but everyone is using them now. Why is not everyone using rule based model transformation languages then? In this thesis, we propose a framework, comprised of a language and its respective environment, designed to tackle the most performance critical operation of high-level model transformation languages: the pattern matching. This framework shows that it is possible to mitigate the performance penalty while still using high-level model transformation languages.

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.

Hotel industry: An answer to the emerging trends on the global demand side of tourism

This dissertation studies essentially how Millennials are changing the hotel industry, in the sense that new trends are emerging with this generation and hotels need to respond accordingly, in order to survive within their competitive industry. Emphasis is also given to Asian travellers, as the enlargement of these countries’ middle class populations is predicted, therefore making Asian travellers a valuable target for the hotel industry. To successfully target this segment, hoteliers need also to consider the cultural differences and aspirations that come together with the Asian travellers, and appropriately adapt their offer to them. I will then redirect this study to the city of Lisbon, the Portuguese capital, to analyse if Lisbon’s four and five-star hotel managers are aware of the new market trends, and to understand how they are changing their hotels in order to make them more attractive to Millennials and Asian travellers. Using a sample of 12 hotels (four and five-stars ratings), I have concluded that, although there is a notable undergoing process of adaptation to these guests, there is a long way ahead in order for Lisbon’s hotels to entirely please and retain millennial guests.

Risk of employing an evolvable production system

Nowadays manufacturing companies are facing a more challenging environment due to the unpredictability of the markets in order to survive. Enterprises need to keep innovating and deliver products with new internal or external characteristics. There are strategies and solutions, to different organisational level from strategic to operational, when technology is growing faster in operational level, more specifically in manufacturing system. This means that companies have to deal with the changes of the emergent manufacturing systems while it can be expensive and not easy to be implement. An agile manufacturing system can help to cope with the markets changeability. Evolvable Production Systems (EPS) is an emergent paradigm which aims to bring new solutions to deal with changeability. The proposed paradigm is characterised by modularity and intends to introduce high flexibility and dynamism at shop floor level through the use of the evolution of new computational devices and technology. This new approach brings to enterprises the ability to plug and unplug new devices and allowing fast reformulation of the production line without reprogramming. There is no doubt about the advantages and benefits of this emerging technology but the feasibility and applicability is still under questioned. Most researches in this area are focused on technical side, explaining the advantages of those systems while there are no sufficient works discussing the implementation risks from different perspective, including business owner. The main objective of this work is to propose a methodology and model to identify, classify and measure potential risk associated with an implementation of this emergent paradigm. To quantify the proposed comprehensive risk model, an Intelligent Decision system is developed employing Fuzzy Inference System to deal with the knowledge of experts, as there are no historical data and sufficient research on this area. The result can be the vulnerability assessment of implementing EPS technology in manufacturing companies when the focus is more on SMEs. The present dissertation used the experts’ knowledge and experiences, who were involved in FP7 project IDEAS, which is one of the leading projects in this area.