The histopathological approach to inflammatory bowel disease: a practice guide

Inflammatory bowel diseases (IBDs) are lifelong disorders predominantly present in developed countries. In their pathogenesis, an interaction between genetic and environmental factors is involved. This practice guide, prepared on behalf of the European Society of Pathology and the European Crohn's and Colitis Organisation, intends to provide a thorough basis for the histological evaluation of resection specimens and biopsy samples from patients with ulcerative colitis or Crohn's disease. Histopathologically, these diseases are characterised by the extent and the distribution of mucosal architectural abnormality, the cellularity of the lamina propria and the cell types present, but these features frequently overlap. If a definitive diagnosis is not possible, the term indeterminate colitis is used for resection specimens and the term inflammatory bowel disease unclassified for biopsies. Activity of disease is reflected by neutrophil granulocyte infiltration and epithelial damage. The evolution of the histological features that are useful for diagnosis is time- and disease-activity dependent: early disease and long-standing disease show different microscopic aspects. Likewise, the histopathology of childhood-onset IBD is distinctly different from adult-onset IBD. In the differential diagnosis of severe colitis refractory to immunosuppressive therapy, reactivation of latent cytomegalovirus (CMV) infection should be considered and CMV should be tested for in all patients. Finally, patients with longstanding IBD have an increased risk for the development of adenocarcinoma. Dysplasia is the universally used marker of an increased cancer risk, but inter-observer agreement is poor for the categories low-grade dysplasia and indefinite for dysplasia. A diagnosis of dysplasia should not be made by a single pathologist but needs to be confirmed by a pathologist with expertise in gastrointestinal pathology.

Adaptive learning in agents behaviour: a framework for electricity markets simulation

Electricity markets are complex environments with very particular characteristics. A critical issue regarding these specific characteristics concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, which was performed so that the competitiveness could be increased, but it also had exponential implications in the increase of the complexity and unpredictability in those markets scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behaviour. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This dissertation presents ALBidS – Adaptive Learning strategic Bidding System, a multiagent system created to provide decision support to market negotiating players. This system is integrated with the MASCEM electricity market simulator, so that its advantage in supporting a market player can be tested using cases based on real markets’ data. ALBidS considers several different methodologies based on very distinct approaches, to provide alternative suggestions of which are the best actions for the supported player to perform. The approach chosen as the players’ actual action is selected by the employment of reinforcement learning algorithms, which for each different situation, simulation circumstances and context, decides which proposed action is the one with higher possibility of achieving the most success. Some of the considered approaches are supported by a mechanism that creates profiles of competitor players. These profiles are built accordingly to their observed past actions and reactions when faced with specific situations, such as success and failure. The system’s context awareness and simulation circumstances analysis, both in terms of results performance and execution time adaptation, are complementary mechanisms, which endow ALBidS with further adaptation and learning capabilities.

Host-symbiont interactions in the deep-sea vent mussel Bathymodiolus azoricus : a molecular approach

Tese de Doutoramento, Ciências do Mar, especialidade de Biologia Marinha, 19 de Dezembro de 2015, Universidade dos Açores.

Capillary bridging and long-range attractive forces in a mean-field approach

When a mixture is confined, one of the phases can condense out. This condensate, which is otherwise metastable in the bulk, is stabilized by the presence of surfaces. In a sphere-plane geometry, routinely used in atomic force microscope and surface force apparatus, it, can form a bridge connecting the surfaces. The pressure drop in the bridge gives rise to additional long-range attractive forces between them. By minimizing the free energy of a binary mixture we obtain the force-distance curves as well as the structural phase diagram of the configuration with the bridge. Numerical results predict a discontinuous transition between the states with and without the bridge and linear force-distance curves with hysteresis. We also show that similar phenomenon can be observed in a number of different systems, e.g., liquid crystals and polymer mixtures. (C). 2004 American Institute of Physics.

Neural-network approach to modeling liquid crystals in complex confinement

Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.

A sustainable approach to the reuse of student - centered learning scenarios

Proceedings of EULEARN09 - Intenational Conference and New Learning Technologies, Barcelona, Spain, 6-8 July

Dominant set approach to ECG biometrics

Electrocardiographic (ECG) signals are emerging as a recent trend in the field of biometrics. In this paper, we propose a novel ECG biometric system that combines clustering and classification methodologies. Our approach is based on dominant-set clustering, and provides a framework for outlier removal and template selection. It enhances the typical workflows, by making them better suited to new ECG acquisition paradigms that use fingers or hand palms, which lead to signals with lower signal to noise ratio, and more prone to noise artifacts. Preliminary results show the potential of the approach, helping to further validate the highly usable setups and ECG signals as a complementary biometric modality.

A waste management school approach towards sustainability

Education towards sustainability in Chemical Engineering (CEng) gave birth to awaste management program (WMP) at Instituto Superior de Engenharia do Porto, in Portugal. It involves students, teachers, and laboratory technicians. It aims to enhance the conscientiousness of the decision-maker next generation for saving resources, managing wastes, and at same time to develop applied chemistry understanding. This program was implemented in 1999 and is responsible for management and fate of all inorganic wastewater providing from training experimental activities of the CEng degree. An immediate reduction of wastes at their source was first defined. Wastes were collected separately and were reused, recycled or chemically treated, and after analytically controlled as legally imposed. Solids formed after this program were recycled, purified or followed suitable elimination. Global results point out environmental, pedagogical, and social benefits. Active participants are aware, in agreement, and publicly committed to the WMP.

How new online communication tools and the availability of content influence the audiences and the creative process

We live in a changing world. At an impressive speed, every day new technological resources appear. We increasingly use the Internet to obtain and share information, and new online communication tools are emerging. Each of them encompasses new potential and creates new audiences. In recent years, we witnessed the emergence of Facebook, Twitter, YouTube and other media platforms. They have provided us with an even greater interactivity between sender and receiver, as well as generated a new sense of community. At the same time we also see the availability of content like it never happened before. We are increasingly sharing texts, videos, photos, etc. This poster intends to explore the potential of using these new online communication tools in the cultural sphere to create new audiences, to develop of a new kind of community, to provide information as well as different ways of building organizations’ memory. The transience of performing arts is accompanied by the need to counter that transience by means of documentation. This desire to ‘save’ events reaches its expression with the information archive of the different production moments as well as the opportunity to record the event and present it through, for instance, digital platforms. In this poster we intend to answer the following questions: which online communication tools are being used to engage audiences in the cultural sphere (specifically between theater companies in Lisbon)? Is there a new relationship with the public? Are online communication tools creating a new kind of community? What changes are these tools introducing in the creative process? In what way the availability of content and its archive contribute to the organization memory? Among several references, we will approach the two-way communication model that James E. Grunig & Todd T. Hunt (1984) already presented and the concept of mass self-communication of Manuel Castells (2010). Castells also tells us that we have moved from traditional media to a system of communication networks. For Scott Kirsner (2010), we have entered an era of digital creativity, where artists have the tools to do what they imagined and the public no longer wants to just consume cultural goods, but instead to have a voice and participate. The creativity process is now depending on the public choice as they wander through the screen. It is the receiver who owns an object which can be exchanged. Virtual reality has encouraged the receiver to abandon its position of passive observer and to become a participant agent, which implies a challenge to organizations: inventing new forms of interfaces. Therefore, we intend to find new and effective online tools that can be used by cultural organizations; the best way to manage them; to show how organizations can create a community with the public and how the availability of online content and its archive can contribute to the organizations’ memory.

Feature selection for clustering categorical data with an embedded modelling approach

Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

A new MILP based approach for unit commitment in power production planning

This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum; this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances, including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective.

Six thinking hats for electricity markets simulation: adapting meeting tools to agent decision

In almost all industrialized countries, the energy sector has suffered a severe restructuring that originated a greater complexity in market players’ interactions. The complexity that these changes brought made way for the creation of decision support tools that facilitate the study and understanding of these markets. MASCEM – “Multiagent Simulator for Competitive Electricity Markets” arose in this context providing a framework for evaluating new rules, new behaviour, and new participants in deregulated electricity markets. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. ALBidS is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM it considers several different methodologies based on very distinct approaches. The Six Thinking Hats is a powerful technique used to look at decisions from different perspectives. This tool’s goal is to force the thinker to move outside his habitual thinking style. It was developed to be used mainly at meetings in order to “run better meetings, make faster decisions”. This dissertation presents a study about the applicability of the Six Thinking Hats technique in Decision Support Systems, particularly with the multiagent paradigm like the MASCEM simulator. As such this work’s proposal is of a new agent, a meta-learner based on STH technique that organizes several different ALBidS’ strategies and combines the distinct answers into a single one that, expectedly, out-performs any of them.

CYCLOTech - an innovative approach for the reliable production of 99mTc - technetium

CYCLOTech is a high-tech Project, related with an innovative method for direct production of a radioactive pharmaceutical, used in excess of 85% of 35 Million Nuclear Medicine procedures done yearly, worldwide, representing globally more than 3 Billion Euros. The CYCLOTech team has developed an innovative proprietary methodology based on the use of Cyclotron Centers, formally identified as the Clients (actually, there are around 450 of this Centers in function worldwide), to directly produce and deliver the radiopharmaceutical to the final users, at the Hospitals and other Health Institutions (estimating at around 25.000, worldwide). The investment still need to finish Research and Technological Development (RTD), Industrial, Regulatory and Intellectual Property Rights (IPR) issues and allow the introduction in the Market is 4,35 M€, with a Payback of 3 years, with an Investment Return Rate (IRR) of 81,7% and a Net Present Value (NPV) of 60.620.525€ (in 2020).

Sustainability reporting and financial reporting: the relevance of an integrated reporting approach

In the business world, there are issues such as globalisation, environmental awareness, and the rising expectations of public opinion which have a specific role in what is required from companies as providers of information to the market. This chapter refers to the current state of corporate reporting (financial reporting and sustainability reporting) and demonstrates the need for evolution to a more integrated method of reporting which meets the stakeholders’ needs. This research offers a reflection on how this development can be achieved, which notes the ongoing efforts by international organisations in implementing the diffusion and adoption, as well as looking at the characteristics which are needed for this type of reporting. It also makes the link between an actual case of a company that is one of the world references in sustainable development and integrated reporting. Whether or not the integrated reporting is the natural evolution of the history of financial and sustainability reporting, it still cannot yet claim to be infallible. However, it may definitely be concluded that a new approach is necessary to meet the needs which are continuously developing for a network of stakeholders.

A semantic approach for learning objects repositories with knowledge reuse

In this paper we discuss how the inclusion of semantic functionalities in a Learning Objects Repository allows a better characterization of the learning materials enclosed and improves their retrieval through the adoption of some query expansion strategies. Thus, we started to regard the use of ontologies to automatically suggest additional concepts when users are filling some metadata fields and add new terms to the ones initially provided when users specify the keywords with interest in a query. Dealing with different domain areas and having considered impractical the development of many different ontologies, we adopted some strategies for reusing ontologies in order to have the knowledge necessary in our institutional repository. In this paper we make a review of the area of knowledge reuse and discuss our approach.