Algorithm for the Parkinson’s disease behavioural models characterization using a biosensor

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

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.

Models of human behaviour in social-ecological systems

Environmental change research often relies on simplistic, static models of human behaviour in social-ecological systems. This limits understanding of how social-ecological change occurs. Integrative, process-based behavioural models, which include feedbacks between action, and social and ecological system structures and dynamics, can inform dynamic policy assessment in which decision making is internalised in the model. These models focus on dynamics rather than states. They stimulate new questions and foster interdisciplinarity between and within the natural and social sciences.

Behavioural analysis of mouse mutants with altered neuronal and glial genes

Im ersten Teil dieser Doktorarbeit beabsichtigte meine Arbeit, die funktionelle Beteiligung des CB1 Rezeptors, einer Hauptkomponente des neuronalen Endocannabinoid-Systems (ECS), an der Ausbildung von verschiedenen Verhaltensphänotypen mit Hilfe von konditionalen Mausmutanten, denen der CB1 Rezeptor auf verschiedenen neuronalen Unterpopulationen fehlt, aufzuschlüsseln und zu untersuchen. Verschiedene Verhaltensmodelle wurden hierzu getestet. Dabei lag der Fokus dieser Arbeit auf der CB1f/f;D1-Cre Mauslinie, welche der CB1 Rezeptor auf den D1 Rezeptor exprimierenden Neuronen des Striatums fehlt. Ich konnte zeigen, dass der Verlust des CB1 Rezeptors auf diesen Neuronen keinen Einfluss auf basale neurologische Funktionen, Gewicht, Bewegung, Exploration, Sozialverhalten, Angst und Stressbewältigung der Tiere hat, jedoch eine Beteiligung an der Entwicklung von Suchtverhalten gegeben ist. Bei Betrachtung des Kokain-induzierten Suchtverhaltens zeigten die konditionalen Mausmutanten eine reduzierte Suchtanfälligkeit sowohl im Vergleich zu Tieren mit einem totalen CB1 Rezeptor Verlust in allen Körperzellen, als auch zu genetisch unveränderten Kontrollmäusen beider Linien.rnDes Weiteren zeigen die Ergebnisse dieser Studie eine große, aber gegensätzliche Beteiligung des ECS bei der Regulation von Exploration in Abhängigkeit des Verlustes des CB1 Rezeptors auf GABAergen Neuronen des Vorderhirns und kortikalen glutamatergen Neuronen, jedoch nicht auf striatalen Neuronen alleine. Zusätzlich war ich in der Lage, die Wichtigkeit des genetischen Hintergrunds von Mauslinien nicht nur auf die Ausbildung von spezifischen Verhaltensphänotypen, sondern auch auf die Genexpression zu zeigen.rnIn dem zweiten Teil dieser Arbeit, in dem ich mich auf die Funktion von Gliazellen konzentrierte, wurden ebenfalls Mausmutanten in verschiedenen Verhaltensmodellen getestet. Ein genetisches Auslöschen des NG2 Glykoproteins in Gliazellen sorgt in den Knock-out Mäusen für ein schlechteres Hörvermögen und ein reduziertes Depressionsverhalten im Vergleich zu ihren Wildtyp-Kontrollmäusen. Interessanterweise zeigten diese Tiere auch eine reduzierte Empfänglichkeit bei chemisch induzierten epileptischen Krämpfen, was eine Rolle des NG2 Glykoproteins bei der Kontrolle der glutamatergen Homöostase vorschlägt, die wahrscheinlich durch Strukturänderungen der Neuron-Glia-Synapse verursacht wird. rn

Puolustusrutiinit organisaation oppimisessa

Tutkimuksessa selvitettiin Chris Argyriksen käsitettä puolustusrutiinit. Koska niiden tutkimus on jäänyt vähäiseksi, työn tarkoitus oli selvittää, voidaanko kohdeorganisaatiossa osoittaa olevan käyttäytymismalleja, jotka viittaisivat puolustusrutiinien olemassaoloon. Teoriaosassa lukija johdateltiin aiheeseen selvittämällä, kuinka organisaatio on osa ympäröivää maailmaa ja sitten, kuinka tärkeää oppiminen on yrityksen menestymiselle ja olemassaololle. Puolustusrutiinien teoriaa tutkittiin pääasiassa Chris Argyriksen materiaalin avulla. Tutkimus oli laadullinen puolistrukturoitu yksilöhaastattelu valitussa kohdeyrityksessä. Empiriaosuuden alussa kerrottiin haastateltavista sekä kohdeyrityksestä ja tutkimuksen suorittamisesta. Lopuksi haastattelujen tulokset esiteltiin lukijalle. Tutkimuksen tuloksien mukaan kohdeorganisaatiossa voitiin havaita lukuisia tilanteita, joissa puolustusrutiinit vaikuttivat jopa hyvinkin voimakkaasti. Lisäksi eri organisaatiotasojen välillä havaittiin toisistaan poikkeavia näkemyksiä. Siksi organisaation jäsenet eivät pystyneet muodostamaan yhtenäistä käsitystä organisaation toiminnasta ja ongelmista. Tämä vaikeuttaa organisaation oppimista, ympäristön muutokseen reagointia ja lopulta yrityksen menestymistä. (Argyris 1996, 67)

The Anchoring Bias of Investors and the 52-Week High Momentum Strategy in the OMX Helsinki Stock Exchange: Psychological Approach to Market Efficiency

The behavioural finance literature expects systematic and significant deviations from efficiency to persist in securities markets due to behavioural and cognitive biases of investors. These behavioural models attempt to explain the coexistence of intermediate-term momentum and long-term reversals in stock returns based on the systematic violations of rational behaviour of investors. The study investigates the anchoring bias of investors and the profitability of the 52-week momentum strategy (GH henceforward). The relatively highly volatile OMX Helsinki stock exchange is a suitable market for examining the momentum effect, since international investors tend to realise their positions first from the furthest security markets by the time of market turbulence. Empirical data is collected from Thomson Reuters Datastream and the OMX Nordic website. The objective of the study is to provide a throughout research by formulating a self-financing GH momentum portfolio. First, the seasonality of the strategy is examined by taking the January effect into account and researching abnormal returns in long-term. The results indicate that the GH strategy is subject to significantly negative revenues in January, but the strategy is not prone to reversals in long-term. Then the predictive proxies of momentum returns are investigated in terms of acquisition prices and 52-week high statistics as anchors. The results show that the acquisition prices do not have explanatory power over the GH strategy’s abnormal returns. Finally, the efficacy of the GH strategy is examined after taking transaction costs into account, finding that the robust abnormal returns remain statistically significant despite the transaction costs. As a conclusion, the relative distance between a stock’s current price and its 52-week high statistic explains the profits of momentum investing to a high degree. The results indicate that intermediateterm momentum and long-term reversals are separate phenomena. This presents a challenge to current behavioural theories, which model these aspects of stock returns as subsequent components of how securities markets respond to relevant information.

The Human in the Loop: User Participation in Self-Adaptive Software

Self-adaptive software provides a profound solution for adapting applications to changing contexts in dynamic and heterogeneous environments. Having emerged from Autonomic Computing, it incorporates fully autonomous decision making based on predefined structural and behavioural models. The most common approach for architectural runtime adaptation is the MAPE-K adaptation loop implementing an external adaptation manager without manual user control. However, it has turned out that adaptation behaviour lacks acceptance if it does not correspond to a user’s expectations – particularly for Ubiquitous Computing scenarios with user interaction. Adaptations can be irritating and distracting if they are not appropriate for a certain situation. In general, uncertainty during development and at run-time causes problems with users being outside the adaptation loop. In a literature study, we analyse publications about self-adaptive software research. The results show a discrepancy between the motivated application domains, the maturity of examples, and the quality of evaluations on the one hand and the provided solutions on the other hand. Only few publications analysed the impact of their work on the user, but many employ user-oriented examples for motivation and demonstration. To incorporate the user within the adaptation loop and to deal with uncertainty, our proposed solutions enable user participation for interactive selfadaptive software while at the same time maintaining the benefits of intelligent autonomous behaviour. We define three dimensions of user participation, namely temporal, behavioural, and structural user participation. This dissertation contributes solutions for user participation in the temporal and behavioural dimension. The temporal dimension addresses the moment of adaptation which is classically determined by the self-adaptive system. We provide mechanisms allowing users to influence or to define the moment of adaptation. With our solution, users can have full control over the moment of adaptation or the self-adaptive software considers the user’s situation more appropriately. The behavioural dimension addresses the actual adaptation logic and the resulting run-time behaviour. Application behaviour is established during development and does not necessarily match the run-time expectations. Our contributions are three distinct solutions which allow users to make changes to the application’s runtime behaviour: dynamic utility functions, fuzzy-based reasoning, and learning-based reasoning. The foundation of our work is a notification and feedback solution that improves intelligibility and controllability of self-adaptive applications by implementing a bi-directional communication between self-adaptive software and the user. The different mechanisms from the temporal and behavioural participation dimension require the notification and feedback solution to inform users on adaptation actions and to provide a mechanism to influence adaptations. Case studies show the feasibility of the developed solutions. Moreover, an extensive user study with 62 participants was conducted to evaluate the impact of notifications before and after adaptations. Although the study revealed that there is no preference for a particular notification design, participants clearly appreciated intelligibility and controllability over autonomous adaptations.

The impact of buffer zone size and management on illegal extraction, park protection and enforcement

Many protected areas or parks in developing countries have buffer zones at their boundaries to achieve the dual goals of protecting park resources and providing resource benefits to neighbouring people. Despite the prevalence of these zoning policies, few behavioural models of people’s buffer zone use inform the sizing and management of those zones. This paper uses a spatially explicit resource extraction model to examine the impact of buffer zone size and management on extraction by local people, both legal and illegal, and the impact of that extraction on forest quality in the park’s core and buffer zone. The results demonstrate trade-offs between the level of enforcement, the size of a buffer zone, and the amount of illegal extraction in the park; and describe implications for “enrichment” of buffer zones and evaluating patterns of forest degradation.

Design Strategies and Modelling of Low-Power Sigma-Delta Analog-to-Digital Converters

Oggi, i dispositivi portatili sono diventati la forza trainante del mercato consumer e nuove sfide stanno emergendo per aumentarne le prestazioni, pur mantenendo un ragionevole tempo di vita della batteria. Il dominio digitale è la miglior soluzione per realizzare funzioni di elaborazione del segnale, grazie alla scalabilità della tecnologia CMOS, che spinge verso l'integrazione a livello sub-micrometrico. Infatti, la riduzione della tensione di alimentazione introduce limitazioni severe per raggiungere un range dinamico accettabile nel dominio analogico. Minori costi, minore consumo di potenza, maggiore resa e una maggiore riconfigurabilità sono i principali vantaggi dell'elaborazione dei segnali nel dominio digitale. Da più di un decennio, diverse funzioni puramente analogiche sono state spostate nel dominio digitale. Ciò significa che i convertitori analogico-digitali (ADC) stanno diventando i componenti chiave in molti sistemi elettronici. Essi sono, infatti, il ponte tra il mondo digitale e analogico e, di conseguenza, la loro efficienza e la precisione spesso determinano le prestazioni globali del sistema. I convertitori Sigma-Delta sono il blocco chiave come interfaccia in circuiti a segnale-misto ad elevata risoluzione e basso consumo di potenza. I tools di modellazione e simulazione sono strumenti efficaci ed essenziali nel flusso di progettazione. Sebbene le simulazioni a livello transistor danno risultati più precisi ed accurati, questo metodo è estremamente lungo a causa della natura a sovracampionamento di questo tipo di convertitore. Per questo motivo i modelli comportamentali di alto livello del modulatore sono essenziali per il progettista per realizzare simulazioni veloci che consentono di identificare le specifiche necessarie al convertitore per ottenere le prestazioni richieste. Obiettivo di questa tesi è la modellazione del comportamento del modulatore Sigma-Delta, tenendo conto di diverse non idealità come le dinamiche dell'integratore e il suo rumore termico. Risultati di simulazioni a livello transistor e dati sperimentali dimostrano che il modello proposto è preciso ed accurato rispetto alle simulazioni comportamentali.

Priming moral self-ambivalence heightens deliberative behaviour in self-ambivalent individuals

Background: Recent work on cognitive-behavioural models of obsessive-compulsive disorder has focused on the roles played by various aspects of self-perception. In particular, moral self-ambivalence has been found to be associated with obsessive-compulsive phenomena. Aims: In this study we used an experimental task to investigate whether artificially priming moral self-ambivalence would increase participants' deliberation on ethical problems, an index that might be analogous to obsessive-compulsive behaviour. Method: Non-clinical participants completed two online tasks designed to prime either moral self-ambivalence, general uncertainty, or neither. All participants then completed a task requiring them to consider solutions to moral dilemmas. We recorded the time participants took to respond to the dilemmas and the length of their responses; we then combined these variables to create a measure of deliberation. Results: Priming moral self-ambivalence led to increases in deliberation, but this was only significant among those participants who scored highly on a baseline measure of moral self-ambivalence. Priming general uncertainty had no significant effect upon deliberation. Conclusions: The results suggest that moral self-ambivalence may play a role in the maintenance of obsessive-compulsive behaviour. We propose that individuals who are morally self-ambivalent might respond to situations in which this ambivalence is made salient by exhibiting behaviour with obsessive-compulsive characteristics. These findings have implications for the incorporation of ideas about self-concept into theories of obsessive-compulsive disorder.

Do Children's Health Resources Differ According to Preschool Physical Activity Programmes and Parental Behaviour? A Mixed Methods Study

Preschool can have positive effects on the development of a healthy lifestyle. The present study analysed to what extent different conditions, structures and behavioural models in preschool and family-children's central social microsystems-can lead to differences in children's health resources. Using a cross-sectional mixed methods approach, contrast analyses of "preschools with systematic physical activity programmes" versus "preschools without physical activity programmes" were conducted to assess the extent to which children's physical activity, quality of life and social behaviour differ between preschools with systematic and preschools without physical activity programmes. Differences in children's physical activity according to parental behaviour were likewise assessed. Data on child-related outcomes and parent-related factors were collected via parent questionnaires and child interviews. A qualitative focused ethnographic study was performed to obtain deeper insight into the quantitative survey data. Two hundred and twenty seven (227) children were interviewed at 21 preschools with systematic physical activity programmes, and 190 at 25 preschools without physical activity programmes. There was no significant difference in children's physical activity levels between the two preschool types (p = 0.709). However, the qualitative data showed differences in the design and quality of programmes to promote children's physical activity. Data triangulation revealed a strong influence of parental behaviour. The triangulation of methods provided comprehensive insight into the nature and extent of physical activity programmes in preschools and made it possible to capture the associations between systematic physical activity promotion and children's health resources in a differential manner.

PCA 4 DCA: the application of principal component analysis to the Dendritic Cell Algorithm

As one of the newest members in the field of articial immune systems (AIS), the Dendritic Cell Algorithm (DCA) is based on behavioural models of natural dendritic cells (DCs). Unlike other AIS, the DCA does not rely on training data, instead domain or expert knowledge is required to predetermine the mapping between input signals from a particular instance to the three categories used by the DCA. This data preprocessing phase has received the criticism of having manually over-fitted the data to the algorithm, which is undesirable. Therefore, in this paper we have attempted to ascertain if it is possible to use principal component analysis (PCA) techniques to automatically categorise input data while still generating useful and accurate classication results. The integrated system is tested with a biometrics dataset for the stress recognition of automobile drivers. The experimental results have shown the application of PCA to the DCA for the purpose of automated data preprocessing is successful.

Subgroup relations: A comparison of mutual intergroup differentiation and common ingroup identity models of prejudice reduction

Two studies examined relations between groups (humanities and math-science students) that implicitly or explicitly share a common superordinate category (university student). In Experiment 1, 178 participants performed a noninteractive decision-making task during which category salience was manipulated in a 2 (superordinate category salience) x 2 (subordinate category salience) between-groups design. Consistent with the mutual intergroup differentiation model, participants for whom both categories were salient exhibited the lowest levels of bias, whereas bias was strongest when the superordinate category alone was made salient. This pattern of results was replicated in Experiment 2 (N = 135). In addition, Experiment 2 demonstrated that members of subgroups that are nested within a superordinate category are more sensitive to how the superordinate category is represented than are members of subgroups that extend beyond the boundaries of the superordinate category.