Purification of complex biopharmaceuticals with new processes, advanced analytics and computer-aided process design tools

Dissertação para obtenção do Grau de Mestre em Biotecnologia

Optimization of investment promotion tools for Portugal: Specific recommendations to attract investments from Germany

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

Introduction: digital methods and tools for historical research

As an introduction to a series of articles focused on the exploration of particular tools and/or methods to bring together digital technology and historical research, the aim of this paper is mainly to highlight and discuss in what measure those methodological approaches can contribute to improve analytical and interpretative capabilities available to historians. In a moment when the digital world present us with an ever-increasing variety of tools to perform extraction, analysis and visualization of large amounts of text, we thought it would be relevant to bring the digital closer to the vast historical academic community. More than repeating an idea of digital revolution introduced in the historical research, something recurring in the literature since the 1980s, the aim was to show the validity and usefulness of using digital tools and methods, as another set of highly relevant tools that the historians should consider. For this several case studies were used, combining the exploration of specific themes of historical knowledge and the development or discussion of digital methodologies, in order to highlight some changes and challenges that, in our opinion, are already affecting the historians' work, such as a greater focus given to interdisciplinarity and collaborative work, and a need for the form of communication of historical knowledge to become more interactive.

Machine learning Gaussian short rate

Dissertação para obtenção do Grau de Doutor em Estatística e Gestão do Risco

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.

Machine diagnosis based on artificial immune systems

Nowadays, many of the manufactory and industrial system has a diagnosis system on top of it, responsible for ensuring the lifetime of the system itself. It achieves this by performing both diagnosis and error recovery procedures in real production time, on each of the individual parts of the system. There are many paradigms currently being used for diagnosis. However, they still fail to answer all the requirements imposed by the enterprises making it necessary for a different approach to take place. This happens mostly on the error recovery paradigms since the great diversity that is nowadays present in the industrial environment makes it highly unlikely for every single error to be fixed under a real time, no production stop, perspective. This work proposes a still relatively unknown paradigm to manufactory. The Artificial Immune Systems (AIS), which relies on bio-inspired algorithms, comes as a valid alternative to the ones currently being used. The proposed work is a multi-agent architecture that establishes the Artificial Immune Systems, based on bio-inspired algorithms. The main goal of this architecture is to solve for a resolution to the error currently detected by the system. The proposed architecture was tested using two different simulation environment, each meant to prove different points of views, using different tests. These tests will determine if, as the research suggests, this paradigm is a promising alternative for the industrial environment. It will also define what should be done to improve the current architecture and if it should be applied in a decentralised system.

Molecular tools in the diagnostic and epidemiology of infections caused by members of Mycobacterium avium Complex

Mycobacterium avium Complex (MAC) comprises microorganisms that affect a wide range of animals including humans. The most relevant are Mycobacterium avium subspecies hominissuis (Mah) with a high impact on public health affecting mainly immunocompromised individuals and Mycobacterium avium subspecies paratuberculosis (Map) causing paratuberculosis in animals with a high economic impact worldwide. In this work, we characterized 28 human and 67 porcine Mah isolates and evaluated the relationship among them by Multiple-Locus Variable number tandem repeat Analysis (MLVA). We concluded that Mah population presented a high genetic diversity and no correlations were inferred based on geographical origin, host or biological sample. For the first time in Portugal Map strains, from asymptomatic bovine faecal samples were isolated highlighting the need of more reliable and rapid diagnostic methods for Map direct detection. Therefore, we developed an IS900 nested real time PCR with high sensitivity and specificity associated with optimized DNA extraction methodologies for faecal and milk samples. We detected 83% of 155 faecal samples from goats, cattle and sheep, and 26% of 98 milk samples from cattle, positive for Map IS900 nested real time PCR. A novel SNPs (single nucleotide polymorphisms) assay to Map characterization based on a Whole Genome Sequencing analysis was developed to elucidate the genetic relationship between strains. Based on sequential detection of 14 SNPs and on a decision tree we were able to differentiate 14 phylogenetic groups with a higher discriminatory power compared to other typing methods. A pigmented Map strain was isolated and characterized evidencing for the first time to our knowledge the existence of pigmented Type C strains. With this work, we intended to improve the ante mortem direct molecular detection of Map, to conscientiously aware for the existence of Map animal infections widespread in Portugal and to contribute to the improvement of Map and Mah epidemiological studies.

Unilever food solutions new digital CRM platform- what is the combination of tools, processes and content that will help Unilever food solutions grow his business?

Unilever Food Solutions new digital CRM1 Platform - What is the combination of tools, processes and content that will help Unilever Food Solutions grow his business? Unilever Food Solutions (UFS) intend to create a new online platform to enable it to communicate with segments of the markets, which have previously been too difficult to reach. Specifically targeted at Chefs and other food professionals, the aim is to create an interactive website, which delivers value to its intended users by providing a variety of relevant content and functions, while simultaneously opening up a potential transactional channel to those same users.

New tools for old organelles

For hundreds of years biologists have studied the naturally occurring diversity in plant and animal species. The invention of the electron microscope in the rst half of the 1900's reveled that cells also can be incredible complex (and often stunningly beautiful). However, despite the fact that the eld of cell biology has existed for over 100 years we still lack a formal understanding of how cells evolve: It is unclear what the extents are in cell and organelle morphology, if and how diversity might be constrained, and how organelles change morphologically over time.(...)