Uncertainty, generalization, and neural representation of relevant variables for decision making

Dissertation presented to obtain the Ph.D degree in Biology, Computational Biology.

UNCERTAINTY AND DECISION-MAKING IN THE HUMAN BRAIN

Dissertation presented to obtain the Ph.D degree in Biology, Neuroscience

Clearing the cloudy crystal balls: Hybrid modelling for energy and climate change mitigation scenarios – A case study for Portugal

Dissertação para obtenção do Grau de Doutor em Ambiente

Interactive spatial decision support for sustainable agroforestry management: a case study in East Kalimantan, Indonesia

Forest managers, stakeholders and investors want to be able to evaluate economic, environmental and social benefits in order to improve the outcomes of their decisions and enhance sustainable forest management. This research developed a spatial decision support system that provides: (1) an approach to identify the most beneficial locations for agroforestry projects based on the biophysical properties and evaluate its economic, social and environmental impact; (2) a tool to inform prospective investors and stakeholders of the potential and opportunities for integrated agroforestry management; (3) a simulation environment that enables evaluation via a dashboard with the opportunity to perform interactive sensitivity analysis for key parameters of the project; (4) a 3D interactive geographic visualization of the economic, environmental and social outcomes, which facilitate understanding and eases planning. Although the tool and methodology presented are generic, a case study was performed in East Kalimantan, Indonesia. For the whole study area, it was simulated the most suitable location for three different plantation schemes: monoculture of timber, a specific recipe (cassava, banana and sugar palm) and different recipes per geographic unit. The results indicate that a mixed cropping plantation scheme, with different recipes applied to the most suitable location returns higher economic, environmental and social benefits.

Toxicity of carcinogenic and non-carcinogenic Polycyclic Aromatic Hydrocarbons and their mixtures to aquatic organisms under ecologically-relevant scenarios

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous priority pollutants that tend to be trapped in aquatic sediments due to their high hydrophobicity. Nonetheless, the differential toxicological effects and mechanisms between the various classes of PAHs and their mixtures, as they invariably occur in the environment, are scarcely known, especially under ecologically-relevant scenarios. This thesis aimed at establishing a bridge between the study of mechanistic pathways and environmental monitoring of carcinogenic and non-carcinogenic PAHs, by introducing ecological-relevance in the research with model PAHs. A first bioassay conducted in situ with the mussel Mytilus edulis demonstrated that, dredging operations in harbours increase PAH bioavailability, eliciting genotoxicity, and showed that established environmental guidelines underestimate risk. Subsequent ex situ bioassays were performed with the carcinogenic benzo[b]fluoranthene (B[b]F) and non-carcinogenic phenantrene (Phe), selected following preceding results, and revealed that low-moderate concentrations of these PAHs in spiked sediments induce genotoxic effects to the clam Ruditapes decussatus, therefore contradicting the general notion that bivalves are less sensitive to PAHs than vertebrates due to inefficient bioactivation. Also, it was demonstrated that passive samplers permit inferring on PAH bioavailability but not on bioaccumulation or toxic effects. On the other hand, sea basses (Dicentrarchus labrax), yielded a complex pattern of effects and responses, relatively to genotoxicity, oxidative stress and production of specific metabolites, especially when exposed to mixtures of the PAHs which led to additive, if not synergistic, effects. It was shown that Phe may elicit significant genotoxicity especially in presence of B[b]F, even though the low, albeit realistic, exposure concentrations diluted dose- and time-independent relationships. The present work demonstrated that environmental quality guidelines underestimate the effects of PAHs in realistic scenarios and showed that the significant genotoxic and histopathological effects caused by mixed PAHs may not be reflected by oxidative stress- or CYP-related biomarkers. Besides important findings on the metabolism of PAH mixtures, the work calls for the need to re-evaluate the criteria for assessing risk and for the disclosure of more efficient indicators of toxicological hazard.

The use of analytical hierarchy process in spatial decision support system for land use management

Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.

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.

Support in decision-making under uncertainty: a project risk assessment tool development and supplementary advances

A foremost dispute that persists on the contemporary world’s agenda is change. The on-going social/technological/economic changes create a competitive and challenging environment for companies to endure. To benefit from these changes, world economies partially depend on emerging Small and Medium Enterprises (SMEs) and their adaptability skills, and subsequently the development of an integrated capability to innovate has become the prime strategy for most of SMEs to subsist and grow. However, innovation and change are always somewhat bonded to an inherent risk development, which subsequently brings on the necessity of a revision of risk management approaches in innovative processes, whose importance SMEs tend to disregard. Additionally, little efforts have been made to improve and create empirical models, metrics and tools to assist SMEs managing latent risks in their innovative projects. This work seeks to present and discuss a solution to support SMEs in engaging on systematic risk management practices, which consists on an integrated risk assessment and response support web-based tool - Spotrisk® - designed for SMEs. On the other hand, an inherent subjectivity is linked with risk management and identification processes, due to uncertainty trait of its nature, for each individual perceives situations according to his own idiosyncrasy, which brings complications in normalizing risk profiles and procedures. This essay aims to bring insights concerning the support in decision-making processes under uncertainty, by addressing issues related with the risk behavior character among individuals. To address such issues, subjects of neuroscience or psychology are explored and models to identify such character are proposed, as well as models to improve presented tool. This work attempts to go beyond the restrictive aim of endeavoring on technical improvement dissertation, and in embraces an exploratory conceptualization concerning micro, small and medium businesses’ traits regarding risk characters and project risk assessment tools.

Foresight exercises as a tool for decision-making: the example of two case studies in health

Based on the report for the unit “Foresight Methods Analysis” of the PhD programme on Technology Assessment at the Universidade Nova de Lisboa, under the supervision of Prof. Dr. António B. Moniz

Machine ethics via logic programming

Machine ethics is an interdisciplinary field of inquiry that emerges from the need of imbuing autonomous agents with the capacity of moral decision-making. While some approaches provide implementations in Logic Programming (LP) systems, they have not exploited LP-based reasoning features that appear essential for moral reasoning. This PhD thesis aims at investigating further the appropriateness of LP, notably a combination of LP-based reasoning features, including techniques available in LP systems, to machine ethics. Moral facets, as studied in moral philosophy and psychology, that are amenable to computational modeling are identified, and mapped to appropriate LP concepts for representing and reasoning about them. The main contributions of the thesis are twofold. First, novel approaches are proposed for employing tabling in contextual abduction and updating – individually and combined – plus a LP approach of counterfactual reasoning; the latter being implemented on top of the aforementioned combined abduction and updating technique with tabling. They are all important to model various issues of the aforementioned moral facets. Second, a variety of LP-based reasoning features are applied to model the identified moral facets, through moral examples taken off-the-shelf from the morality literature. These applications include: (1) Modeling moral permissibility according to the Doctrines of Double Effect (DDE) and Triple Effect (DTE), demonstrating deontological and utilitarian judgments via integrity constraints (in abduction) and preferences over abductive scenarios; (2) Modeling moral reasoning under uncertainty of actions, via abduction and probabilistic LP; (3) Modeling moral updating (that allows other – possibly overriding – moral rules to be adopted by an agent, on top of those it currently follows) via the integration of tabling in contextual abduction and updating; and (4) Modeling moral permissibility and its justification via counterfactuals, where counterfactuals are used for formulating DDE.

Decision-making process of Nova Executivos’ students

Field lab: Consumer insights

Importance of decision-making in a purchasing context – DPS Case Study

This work project has the objective of exploring the importance of making good decisions on supplier selection, so that the purchasing department can contribute to the success of a company. For that it is presented a short bibliography review of the latest insights that were found relevant, on the subjects of purchasing, technology, outsourcing, supplier selection and decision-making techniques. For a better understating on how to deal with a decision-making situation, a case study is also presented: Digital Printing Solutions (DPS) is a Portuguese company that provides complete and integrated printing solutions and has been planning to contract a software supplier. DPS has no formal supplier-selection model and it has to choose between 2 suppliers. The case study was solved using the M-MACBETH software. I have found that complex decisions-making situations can be easily overcome by using the M-MACBETH decision model. Moreover, the usage of a model, instead of decision that follows no formal procedure, provides the decision maker with insights that can be useful to negotiate with the supplier.

How to improve consumer decision skills in children? A case study of an intervention with institutionalized children

The aim of this study is to assess the institutionalized children’s skills as consumers but also to assess how we can improve their knowledge through an intervention. The sample was composed of two subgroups (38 institutionalized children and 36 non-institutionalized children). In order to assess children’s knowledge, a questionnaire and an interview were used. The method used as intervention was a 30-minute class. Results suggested that institutionalized children have lower levels of knowledge regarding consumption-related practices and lower levels of accuracy at estimating prices than non-institutionalized children. However, results also showed that the attitudes of institutionalized children towards advertising and making decisions based on price/quantity evaluation or based on the use of the same strategy in different situations are not significantly different from the non-institutionalized children. Regarding the intervention, it was possible to conclude that one class is not the best method to improve children’s knowledge. Institutionalized children need a longer and more practical intervention.

Challenges of converting nonprofit in for-profit-reasons decision making and key success factores of a conversion

Due to external constraints (opposed by the market and legal system) and internal changes nonprofit organizations have been converting to for-profit entities combining commercial revenue and social value creation. To create an understanding of the conversion process considering its challenges, the reasons, the decision-making process and key success factors of a conversion are examined. Therefore, a two-step research procedure is used combining literature research and a multiple case study approach based on expert interviews with known companies. The outcome is a helpful guideline (including a decision matrix) for social entrepreneurs that might face a conversion.