Predicting the impacts of climate change on the distribution and conservation of endemic forest land snails of Madeira Island

Climate change is emerging as one of the major threats to natural communities of the world’s ecosystems; and biodiversity hotspots, such as Madeira Island, might face a challenging future in the conservation of endangered land snails’ species. With this thesis, progresses have been made in order to properly understand the impact of climate on these vulnerable taxa; and species distribution models coupled with GIS and climate change scenarios have become crucial to understand the relations between species distribution and environmental conditions, identifying threats and determining biodiversity vulnerability. With the use of MaxEnt, important changes in the species suitable areas were obtained. Laurel forest species, highly dependent on precipitation and relative humidity, may face major losses on their future suitable areas, leading to the possible extinction of several endangered species, such as Leiostyla heterodon. Despite the complexity of the biological systems, the intrinsic uncertainty of species distribution models and the lack of information about land snails’ functional traits, this analysis contributed to a pioneer study on the impacts of climate change on endemic species of Madeira Island. The future inclusion of predictions of the effect of climate change on species distribution as part of IUCN assessments could contribute to species prioritizing, promoting specific management actions and maximizing conservation investment.

Amyotrophic Lateral Sclerosis:Mammalian Cell Models,Copper-Zinc Superoxide Dismutaseand Biological Characteristics

"Amyotrophic Lateral Sclerosis (ALS) is the most severe and common adult onset disorder that affects motor neurons in the spinal cord, brainstem and cortex, resulting in progressive weakness and death from respiratory failure within two to five years of symptoms onset(...)

Enterprise reference lexicon building from business models

Nowadays, a significant increase on the demand for interoperable systems for exchanging data in business collaborative environments has been noticed. Consequently, cooperation agreements between each of the involved enterprises have been brought to light. However, due to the fact that even in a same community or domain, there is a big variety of knowledge representation not semantically coincident, which embodies the existence of interoperability problems in the enterprises information systems that need to be addressed. Moreover, in relation to this, most organizations face other problems about their information systems, as: 1) domain knowledge not being easily accessible by all the stakeholders (even intra-enterprise); 2) domain knowledge not being represented in a standard format; 3) and even if it is available in a standard format, it is not supported by semantic annotations or described using a common and understandable lexicon. This dissertation proposes an approach for the establishment of an enterprise reference lexicon from business models. It addresses the automation in the information models mapping for the reference lexicon construction. It aggregates a formal and conceptual representation of the business domain, with a clear definition of the used lexicon to facilitate an overall understanding by all the involved stakeholders, including non-IT personnel.

Learning facial-expression models with crowdsourcing

The computational power is increasing day by day. Despite that, there are some tasks that are still difficult or even impossible for a computer to perform. For example, while identifying a facial expression is easy for a human, for a computer it is an area in development. To tackle this and similar issues, crowdsourcing has grown as a way to use human computation in a large scale. Crowdsourcing is a novel approach to collect labels in a fast and cheap manner, by sourcing the labels from the crowds. However, these labels lack reliability since annotators are not guaranteed to have any expertise in the field. This fact has led to a new research area where we must create or adapt annotation models to handle these weaklylabeled data. Current techniques explore the annotators’ expertise and the task difficulty as variables that influences labels’ correction. Other specific aspects are also considered by noisy-labels analysis techniques. The main contribution of this thesis is the process to collect reliable crowdsourcing labels for a facial expressions dataset. This process consists in two steps: first, we design our crowdsourcing tasks to collect annotators labels; next, we infer the true label from the collected labels by applying state-of-art crowdsourcing algorithms. At the same time, a facial expression dataset is created, containing 40.000 images and respective labels. At the end, we publish the resulting dataset.

Real-time collaborative editing of OutSystems DSL models

Real-time collaborative editing systems are common nowadays, and their advantages are widely recognized. Examples of such systems include Google Docs, ShareLaTeX, among others. This thesis aims to adopt this paradigm in a software development environment. The OutSystems visual language lends itself very appropriate to this kind of collaboration, since the visual code enables a natural flow of knowledge between developers regarding the developed code. Furthermore, communication and coordination are simplified. This proposal explores the field of collaboration on a very structured and rigid model, where collaboration is made through the copy-modify-merge paradigm, in which a developer gets its own private copy from the shared repository, modifies it in isolation and later uploads his changes to be merged with modifications concurrently produced by other developers. To this end, we designed and implemented an extension to the OutSystems Platform, in order to enable real-time collaborative editing. The solution guarantees consistency among the artefacts distributed across several developers working on the same project. We believe that it is possible to achieve a much more intense collaboration over the same models with a low negative impact on the individual productivity of each developer.

The Portuguese contemporary art as an investment

In this paper we investigate what drives the prices of Portuguese contemporary art at auction and explore the potential of art as an asset. Based on a hedonic prices model we construct an Art Price Index as a proxy for the Portuguese contemporary art market over the period of 1994 to 2014. A performance analysis suggests that art underperforms the S&P500 but overperforms the Portuguese stock market and American Government bonds. However, It does it at the cost of higher risk. Results also show that art as low correlation with financial markets, evidencing some potential in risk mitigation when added to traditional equity portfolios.

Development of 3D in vitro models for prediction of hepatic metabolism and toxicity

The development of human cell models that recapitulate hepatic functionality allows the study of metabolic pathways involved in toxicity and disease. The increased biological relevance, cost-effectiveness and high-throughput of cell models can contribute to increase the efficiency of drug development in the pharmaceutical industry. Recapitulation of liver functionality in vitro requires the development of advanced culture strategies to mimic in vivo complexity, such as 3D culture, co-cultures or biomaterials. However, complex 3D models are typically associated with poor robustness, limited scalability and compatibility with screening methods. In this work, several strategies were used to develop highly functional and reproducible spheroid-based in vitro models of human hepatocytes and HepaRG cells using stirred culture systems. In chapter 2, the isolation of human hepatocytes from resected liver tissue was implemented and a liver tissue perfusion method was optimized towards the improvement of hepatocyte isolation and aggregation efficiency, resulting in an isolation protocol compatible with 3D culture. In chapter 3, human hepatocytes were co-cultivated with mesenchymal stem cells (MSC) and the phenotype of both cell types was characterized, showing that MSC acquire a supportive stromal function and hepatocytes retain differentiated hepatic functions, stability of drug metabolism enzymes and higher viability in co-cultures. In chapter 4, a 3D alginate microencapsulation strategy for the differentiation of HepaRG cells was evaluated and compared with the standard 2D DMSO-dependent differentiation, yielding higher differentiation efficiency, comparable levels of drug metabolism activity and significantly improved biosynthetic activity. The work developed in this thesis provides novel strategies for 3D culture of human hepatic cell models, which are reproducible, scalable and compatible with screening platforms. The phenotypic and functional characterization of the in vitro systems performed contributes to the state of the art of human hepatic cell models and can be applied to the improvement of pre-clinical drug development efficiency of the process, model disease and ultimately, development of cell-based therapeutic strategies for liver failure.

Predicting market direction with hidden Markov models

This paper develops the model of Bicego, Grosso, and Otranto (2008) and applies Hidden Markov Models to predict market direction. The paper draws an analogy between financial markets and speech recognition, seeking inspiration from the latter to solve common issues in quantitative investing. Whereas previous works focus mostly on very complex modifications of the original hidden markov model algorithm, the current paper provides an innovative methodology by drawing inspiration from thoroughly tested, yet simple, speech recognition methodologies. By grouping returns into sequences, Hidden Markov Models can then predict market direction the same way they are used to identify phonemes in speech recognition. The model proves highly successful in identifying market direction but fails to consistently identify whether a trend is in place. All in all, the current paper seeks to bridge the gap between speech recognition and quantitative finance and, even though the model is not fully successful, several refinements are suggested and the room for improvement is significant.

Knowledge management framework based on brain models and human physiology

The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.

Flood resilient housing recovery models: a theoretical case study in Maldives

Natural disasters are events that cause general and widespread destruction of the built environment and are becoming increasingly recurrent. They are a product of vulnerability and community exposure to natural hazards, generating a multitude of social, economic and cultural issues of which the loss of housing and the subsequent need for shelter is one of its major consequences. Nowadays, numerous factors contribute to increased vulnerability and exposure to natural disasters such as climate change with its impacts felt across the globe and which is currently seen as a worldwide threat to the built environment. The abandonment of disaster-affected areas can also push populations to regions where natural hazards are felt more severely. Although several actors in the post-disaster scenario provide for shelter needs and recovery programs, housing is often inadequate and unable to resist the effects of future natural hazards. Resilient housing is commonly not addressed due to the urgency in sheltering affected populations. However, by neglecting risks of exposure in construction, houses become vulnerable and are likely to be damaged or destroyed in future natural hazard events. That being said it becomes fundamental to include resilience criteria, when it comes to housing, which in turn will allow new houses to better withstand the passage of time and natural disasters, in the safest way possible. This master thesis is intended to provide guiding principles to take towards housing recovery after natural disasters, particularly in the form of flood resilient construction, considering floods are responsible for the largest number of natural disasters. To this purpose, the main structures that house affected populations were identified and analyzed in depth. After assessing the risks and damages that flood events can cause in housing, a methodology was proposed for flood resilient housing models, in which there were identified key criteria that housing should meet. The same methodology is based in the US Federal Emergency Management Agency requirements and recommendations in accordance to specific flood zones. Finally, a case study in Maldives – one of the most vulnerable countries to sea level rise resulting from climate change – has been analyzed in light of housing recovery in a post-disaster induced scenario. This analysis was carried out by using the proposed methodology with the intent of assessing the resilience of the newly built housing to floods in the aftermath of the 2004 Indian Ocean Tsunami.

The future of airline business models:

This research is titled “The Future of Airline Business Models: Which Will Win?” and it is part of the requirements for the award of a Masters in Management from NOVA BSE and another from Luiss Guido Carlo University. The purpose is to elaborate a complete market analysis of the European Air Transportation Industry in order to predict which Airlines, strategies and business models may be successful in the next years. First, an extensive literature review of the business model concept has been done. Then, a detailed overview of the main European Airlines and the strategies that they have been implementing so far has been developed. Finally, the research is illustrated with three case studies

Value creation in the nursing home real estate investment market - A case study

The underlying thesis examines the value drivers of direct investments in nursing home real estate in Germany. A survey among investors and operators is conducted in order to identify significant value drivers. Moreover, based on survey results, a framework for assessing German nursing home real estate is developed. This is applied in a case-study about the set-up of a nursing home value-add fund which will demonstrate the value creation process of redeveloping an existing nursing home real estate portfolio. Through a concluding analysis the sources of value creation, sensitivities and future prospects of direct investing into German nursing home real estate are concluded.

Avaliação económica em transplantação renal : abordagem estratégica do processo de doação e análise de custo-utilidade do programa de transplantação renal versus hemodiálise

SUMÁRIO - O desafio atual da Saúde Pública é assegurar a sustentabilidade financeira do sistema de saúde. Em ambiente de recursos escassos, as análises económicas aplicadas à prestação dos cuidados de saúde são um contributo para a tomada de decisão que visa a maximização do bem-estar social sujeita a restrição orçamental. Portugal é um país com 10,6 milhões de habitantes (2011) com uma incidência e prevalência elevadas de doença renal crónica estadio 5 (DRC5), respetivamente, 234 doentes por milhão de habitantes (pmh) e 1.600 doentes/pmh. O crescimento de doenças associadas às causas de DRC, nomeadamente, diabetes Mellitus e hipertensão arterial, antecipam uma tendência para o aumento do número de doentes. Em 2011, dos 17.553 doentes em tratamento substitutivo renal, 59% encontrava-se em programa de hemodiálise (Hd) em centros de diálise extra-hospitalares, 37% viviam com um enxerto renal funcionante e 4% estavam em diálise peritoneal (SPN, 2011). A lista ativa para transplante (Tx) renal registava 2.500 doentes (SPN 2009). O Tx renal é a melhor modalidade terapêutica pela melhoria da sobrevida, qualidade de vida e relação custo-efetividade, mas a elegibilidade para Tx e a oferta de órgãos condicionam esta opção. Esta investigação desenvolveu-se em duas vertentes: i) determinar o rácio custo-utilidade incremental do Tx renal comparado com a Hd; ii) avaliar a capacidade máxima de dadores de cadáver em Portugal, as características e as causas de morte dos dadores potenciais a nível nacional, por hospital e por Gabinete Coordenador de Colheita e Transplantação (GCCT), e analisar o desempenho da rede de colheita de órgãos para Tx. Realizou-se um estudo observacional/não interventivo, prospetivo e analítico que incidiu sobre uma coorte de doentes em Hd que foi submetida a Tx renal. O tempo de seguimento mínimo foi de um ano e máximo de três anos. No início do estudo, colheram-se dados sociodemográficos e clínicos em 386 doentes em Hd, elegíveis para Tx renal. A qualidade de vida relacionada com a saúde (QVRS) foi avaliada nos doentes em Hd (tempo 0) e nos transplantados, aos três, seis, 12 meses, e depois, anualmente. Incluíram-se os doentes que por falência do enxerto renal transitaram para Hd. Na sua medição, utilizou-se um instrumento baseado em preferências da população, o EuroQol-5D, que permite o posterior cálculo dos QALY. Num grupo de 82 doentes, a QVRS em Hd foi avaliada em dois tempos de resposta o que permitiu a análise da sua evolução. Realizou-se uma análise custo-utilidade do Tx renal comparado com a Hd na perspetiva da sociedade. Identificaram-se os custos diretos, médicos e não médicos, e as alterações de produtividade em Hd e Tx renal. Incluíram-se os custos da colheita de órgãos, seleção dos candidatos a Tx renal e follow-up dos dadores vivos. Cada doente transplantado foi utilizado como controle de si próprio em diálise. Avaliou-se o custo médio anual em programa de Hd crónica relativo ao ano anterior à Tx renal. Os custos do Tx foram avaliados prospetivamente. Considerou-se como horizonte temporal o ciclo de vida nas duas modalidades. Usaram-se taxas de atualização de 0%, 3% e 5% na atualização dos custos e QALY e efetuaram-se análises de sensibilidade one way. Entre 2008 e 2010, 65 doentes foram submetidos a Tx renal. Registaram-se, prospetivamente, os resultados em saúde incluíndo os internamentos e os efeitos adversos da imunossupressão, e o consumo dos recursos em saúde. Utilizaram-se modelos de medidas repetidas na avaliação da evolução da QVRS e modelos de regressão múltipla na análise da associação da QVRS e dos custos do transplante com as características basais dos doentes e os eventos clínicos. Comparativamente à Hd, observou-se melhoria da utilidade ao 3º mês de Tx e a qualidade de vida aferida pela escala EQ-VAS melhorou em todos os tempos de observação após o Tx renal. O custo médio da Hd foi de 32.567,57€, considerado uniforme ao longo do tempo. O custo médio do Tx renal foi de 60.210,09€ no 1º ano e 12.956,77€ nos anos seguintes. O rácio custo-utilidade do Tx renal vs Hd crónica foi de 2.004,75€/QALY. A partir de uma sobrevivência do enxerto de dois anos e cinco meses, o Tx associou-se a poupança dos custos. Utilizaram-se os dados nacionais dos Grupos de Diagnóstico Homogéneos e realizou-se um estudo retrospectivo que abrangeu as mortes ocorridas em 34 hospitais com colheita de órgãos, em 2006. Considerou-se como dador potencial o indivíduo com idade entre 1-70 anos cuja morte ocorrera a nível hospitalar, e que apresentasse critérios de adequação à doação de rim. Analisou-se a associação dos dadores potenciais com características populacionais e hospitalares. O desempenho das organizações de colheita de órgãos foi avaliado pela taxa de conversão (rácio entre os dadores potenciais e efetivos) e pelo número de dadores potenciais por milhão de habitantes a nível nacional, regional e por Gabinete Coordenador de Colheita e Transplantação (GCCT). Identificaram-se 3.838 dadores potenciais dos quais 608 apresentaram códigos da Classificação Internacional de Doenças, 9.ª Revisão, Modificações Clínicas (CID- 9-MC) que, com maior frequência, evoluem para a morte cerebral. O modelo logit para dados agrupados identificou a idade, o rácio da lotação em Unidades de Cuidados Intensivos e lotação de agudos, existência de GCCT e de Unidade de Transplantação, e mortalidade por acidente de trabalho como fatores preditivos da conversão dum dador potencial em efetivo e através das estimativas do modelo logit quantificou-se a probabilidade dessa conversão. A doação de órgãos deve ser assumida como uma prioridade e as autoridades em saúde devem assegurar o financiamento dos hospitais com programas de doação, evitando o desperdício de órgãos para transplantação, enquanto um bem público e escasso. A colheita de órgãos deve ser considerada uma opção estratégica da atividade hospitalar orientada para a organização e planeamento de serviços que maximizem a conversão de dadores potenciais em efetivos incluindo esse critério como medida de qualidade e efetividade do desempenho hospitalar. Os resultados deste estudo demonstram que: 1) o Tx renal proporciona ganhos em saúde, aumento da sobrevida e qualidade de vida, e poupança de custos; 2) em Portugal, a taxa máxima de eficácia da conversão dos dadores cadavéricos em dadores potenciais está longe de ser atingida. O investimento na rede de colheita de órgãos para Tx é essencial para assegurar a sustentabilidade financeira e promover a qualidade, eficiência e equidade dos cuidados em saúde prestados na DRC5.

Measuring impact with the social return on investment: the case of the social innovation hub

There is a growing interest in social impact assessment across the private, the public and the nonprofit sector. However, there is still limited academic research produced in this area, particularly in what concerns to the application of the Social Return of Investment (SROI) methodology. The goal of this Work Project is to give an overview of the social impact measurement literature and apply the Social Return on Investment, a flagship methodology to measure impact, to the specific case of the Social Innovation Hub (SIH). The findings suggest that each 1€ invested on the SIH generates 1,21€ in terms of social value. While this value seems very appealing to use, there are some risks in monetizing impact in such way, mainly due to the lack of reliable data available for benchmarking purposes.