Argumentation as Distributed Belief Revision: Conflict Resolution in Decentralised Multi-agent Systems

Decentralised co-operative multi-agent systems are computational systems where conflicts are frequent due to the nature of the represented knowledge. Negotiation methodologies, in this case argumentation based negotiation methodologies, were developed and applied to solve unforeseeable and, therefore, unavoidable conflicts. The supporting computational model is a distributed belief revision system where argumentation plays the decisive role of revision. The distributed belief revision system detects, isolates and solves, whenever possible, the identified conflicts. The detection and isolation of the conflicts is automatically performed by the distributed consistency mechanism and the resolution of the conflict, or belief revision, is achieved via argumentation. We propose and describe two argumentation protocols intended to solve different types of identified information conflicts: context dependent and context independent conflicts. While the protocol for context dependent conflicts generates new consensual alternatives, the latter chooses to adopt the soundest, strongest argument presented. The paper shows the suitability of using argumentation as a distributed decentralised belief revision protocol to solve unavoidable conflicts.

Heat recovery from wastewater: numerical modelling of sewer systems

Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente, perfil Engenharia Sanitária

The role of deviant-letter position in cognate word processing

Dissertação de mestrado integrado em Psicologia

The effects of solvent composition on the affinity of a peptide towards hair keratin: experimental and molecular dynamics data

The study of the interaction between hair filaments and formulations or peptides is of utmost importance in fields like cosmetic research. Keratin intermediate filaments structure is not fully described, limiting the molecular dynamics (MD) studies in this field although its high potential to improve the area. We developed a computational model of a truncated protofibril, simulated its behavior in alcoholic based formulations and with one peptide. The simulations showed a strong interaction between the benzyl alcohol molecules of the formulations and the model, leading to the disorganization of the keratin chains, which regress with the removal of the alcohol molecules. This behavior can explain the increase of peptide uptake in hair shafts evidenced in fluorescence microscopy pictures. The model developed is valid to computationally reproduce the interaction between hair and alcoholic formulations and provide a robust base for new MD studies about hair properties. It is shown that the MD simulations can improve hair cosmetic research, improving the uptake of a compound of interest.

Desenvolvimento de um laboratório pedagógico de vias de comunicação na Universidade do Minho

Dissertação de mestrado integrado em Engenharia Civil

A Foundation System and a State System - Private-School Implications on Welfare and Education Expenditure

This paper examines the effects of two different education - financing systems: a foundation system and a state system on the level and distribution of resources devoted to education in the presence of private schools. We use political economy approach where households differ in their level of income, and the central tax rate used to nance education is determined by a majority vote. Our analysis focuses on implications of allowing for a private-school option. To evaluate the importance of private schools we develop a computational model and calibrate it using USA data. The results reveal that the private school option is very important quantitatively in terms of welfare, total resources spent on education and equity.

The neuronal basis of attention: rate versus synchronization modulation

Extensive theoretical and experimental work on the neuronal correlates of visual attention raises two hypotheses about the underlying mechanisms. The first hypothesis, named biased competition, originates from experimental single-cell recordings that have shown that attention upmodulates the firing rates of the neurons encoding the attended features and downregulates the firing rates of the neurons encoding the unattended features. Furthermore, attentional modulation of firing rates increases along the visual pathway. The other, newer hypothesis assigns synchronization a crucial role in the attentional process. It stems from experiments that have shown that attention modulates gamma-frequency synchronization. In this paper, we study the coexistence of the two phenomena using a theoretical framework. We find that the two effects can vary independently of each other and across layers. Therefore, the two phenomena are not concomitant. However, we show that there is an advantage in the processing of information if rate modulation is accompanied by gamma modulation, namely that reaction times are shorter, implying behavioral relevance for gamma synchronization.

Modeling the impact of lesions in the human brain.

Lesions of anatomical brain networks result in functional disturbances of brain systems and behavior which depend sensitively, often unpredictably, on the lesion site. The availability of whole-brain maps of structural connections within the human cerebrum and our increased understanding of the physiology and large-scale dynamics of cortical networks allow us to investigate the functional consequences of focal brain lesions in a computational model. We simulate the dynamic effects of lesions placed in different regions of the cerebral cortex by recording changes in the pattern of endogenous ("resting-state") neural activity. We find that lesions produce specific patterns of altered functional connectivity among distant regions of cortex, often affecting both cortical hemispheres. The magnitude of these dynamic effects depends on the lesion location and is partly predicted by structural network properties of the lesion site. In the model, lesions along the cortical midline and in the vicinity of the temporo-parietal junction result in large and widely distributed changes in functional connectivity, while lesions of primary sensory or motor regions remain more localized. The model suggests that dynamic lesion effects can be predicted on the basis of specific network measures of structural brain networks and that these effects may be related to known behavioral and cognitive consequences of brain lesions.

Focal dystonia and the Sensory-Motor Integrative Loop for Enacting (SMILE).

Performing accurate movements requires preparation, execution, and monitoring mechanisms. The first two are coded by the motor system, the latter by the sensory system. To provide an adaptive neural basis to overt behaviors, motor and sensory information has to be properly integrated in a reciprocal feedback loop. Abnormalities in this sensory-motor loop are involved in movement disorders such as focal dystonia, a hyperkinetic alteration affecting only a specific body part and characterized by sensory and motor deficits in the absence of basic motor impairments. Despite the fundamental impact of sensory-motor integration mechanisms on daily life, the general principles of healthy and pathological anatomic-functional organization of sensory-motor integration remain to be clarified. Based on the available data from experimental psychology, neurophysiology, and neuroimaging, we propose a bio-computational model of sensory-motor integration: the Sensory-Motor Integrative Loop for Enacting (SMILE). Aiming at direct therapeutic implementations and with the final target of implementing novel intervention protocols for motor rehabilitation, our main goal is to provide the information necessary for further validating the SMILE model. By translating neuroscientific hypotheses into empirical investigations and clinically relevant questions, the prediction based on the SMILE model can be further extended to other pathological conditions characterized by impaired sensory-motor integration.

Stochastic generation of homogeneous isotropic turbulence with well-defined-spectra

A precise and simple computational model to generate well-behaved two-dimensional turbulent flows is presented. The whole approach rests on the use of stochastic differential equations and is general enough to reproduce a variety of energy spectra and spatiotemporal correlation functions. Analytical expressions for both the continuous and the discrete versions, together with simulation algorithms, are derived. Results for two relevant spectra, covering distinct ranges of wave numbers, are given.

Stochastic generation of homogeneous isotropic turbulence with well-defined-spectra

A precise and simple computational model to generate well-behaved two-dimensional turbulent flows is presented. The whole approach rests on the use of stochastic differential equations and is general enough to reproduce a variety of energy spectra and spatiotemporal correlation functions. Analytical expressions for both the continuous and the discrete versions, together with simulation algorithms, are derived. Results for two relevant spectra, covering distinct ranges of wave numbers, are given.

On the role of G protein-coupled receptors oligomerization

The existence of a supramolecular organization of the G protein-coupled receptor (GPCR) is now being widely accepted by the scientific community. Indeed, GPCR oligomers may enhance the diversity and performance by which extracellular signals are transferred to the G proteins in the process of receptor transduction, although the mechanism that underlies this phenomenon still remains unsolved. Recently, it has been proposed that a trans-conformational switching model could be the mechanism allowing direct inhibition/activation of receptor activation/inhibition, respectively. Thus, heterotropic receptor-receptor allosteric regulations are behind the GPCR oligomeric function. In this paper we want to revise how GPCR oligomerization impinges on several important receptor functions like biosynthesis, plasma membrane diffusion or velocity, pharmacology and signaling. In particular, the rationale of receptor oligomerization might lie in the need of sensing complex whole cell extracellular signals and translating them into a simple computational model.

A measure of stability as a criterion for the verification and analysis of simulation models

The aim of this study is to define a new statistic, PVL, based on the relative distance between the likelihood associated with the simulation replications and the likelihood of the conceptual model. Our results coming from several simulation experiments of a clinical trial show that the PVL statistic range can be a good measure of stability to establish when a computational model verifies the underlying conceptual model. PVL improves also the analysis of simulation replications because only one statistic is associated with all the simulation replications. As well it presents several verification scenarios, obtained by altering the simulation model, that show the usefulness of PVL. Further simulation experiments suggest that a 0 to 20 % range may define adequate limits for the verification problem, if considered from the viewpoint of an equivalence test.

AMPc - Sinalização intracelular: um software educacional

Chemicals binding to membrane receptors may induce events within the cell changing its behavior. Since these events are simultaneous and hard to be understood by students, we developed a computational model to dynamically and visually explore the cAMP signaling system to facilitate its understanding. The animation is shown in parts, from the hormone-receptor binding to the cellular response. There are some questions to be answered after using the model. The software was field-tested and an evaluation questionnaire (concerning usability, animations, models, and the software as an educational tool) was answered by the students, showing the software to be a valuable aid for content comprehension.

Towards a lightweight adaptative multicomponential affective recognition system

As part of the Affective Computing research field, the development of automatic affective recognition systems can enhance human-computer interactions by allowing the creation of interfaces that react to the user's emotional state. To that end, this Master Thesis brings affect recognition to nowadays most used human computer interface, mobile devices, by developing a facial expression recognition system able to perform detection under the difficult conditions of viewing angle and illumination that entails the interaction with a mobile device. Moreover, this Master Thesis proposes to combine emotional features detected from expression with contextual information of the current situation, to infer a complex and extensive emotional state of the user. Thus, a cognitive computational model of emotion is defined that provides a multicomponential affective state of the user through the integration of the detected emotional features into appraisal processes. In order to account for individual differences in the emotional experience, these processes can be adapted to the culture and personality of the user.