Objective: To evaluate the 5-year real-world benefit–risk profile of fingolimod in patients with relapsing–remitting MS (RRMS) in Germany. Methods: Post-Authorization Non-interventional German sAfety study of GilEnyA (PANGAEA) is a non-interventional realworld study to prospectively assess the effectiveness and safety of fingolimod in routine clinical practice in Germany. The follow-up period comprised 5 years. Patients were included if they had been diagnosed with RRMS and had been prescribed fingolimod as part of clinical routine. There were no exclusion criteria except the contraindications for fingolimod as defined in the European label. The effectiveness and safety analysis set comprised 4032 and 4067 RRMS patients, respectively. Results: At the time of the 5-year follow-up of PANGAEA, 66.57% of patients still continued fingolimod therapy. Annualized relapse rates decreased from baseline 1.5 ± 1.15 to 0.42 ± 0.734 at year 1 and 0.21 ± 0.483 at year 5, and the disability status remained stable, as demonstrated by the Expanded Disability Status Scale mean change from baseline (0.1 ± 2.51), the decrease of the Multiple Sclerosis Severity Score from 5.1 ± 2.59 at baseline to 3.9 ± 2.31 at the 60-months follow-up, and the percentage of patients with ‘no change’ in the Clinical Global Impression scale at the 60-months follow-up (78.11%). Adverse events (AE) occurring in 75.04% of patients were in line with the known safety profile of fingolimod and were mostly non-serious AE (33.62%) and non-serious adverse drug reactions (50.59%; serious AE 4.98%; serious ADR 10.82%). Conclusions: PANGAEA demonstrated the sustained beneficial effectiveness and safety of fingolimod in the long-term realworld treatment of patients with RRMS.

No description available.

No description available.

The purpose of this dissertation was to test the utility of theories across the development, implementation, and evaluation of three nationwide knowledge translation (KT) interventions in the physical disability community. Using a theory-based evaluation guided by the Theory of Planned Behaviour (TPB), Study 1 evaluates the effectiveness of an evidence-based, continuing education module designed to increase emergency health care professionals’ (HCPs) knowledge and use of clinical practice guidelines for managing patients with spinal cord injury (SCI) who present with autonomic dysrefexia. Findings suggest that behaviour change theory should be integrated into the intervention to change theory-based determinants of behaviour, and that information about intervention implementation may help explain observed outcomes. Study 2 examined the use of theory across three phases of research in the Canadian Paralympic Committee’s Changing Minds, Changing Lives (CMCL) intervention. Study 2.1 describes the restructuring of the CMCL curriculum to include research evidence and theory. Study 2.2 evaluates the short- and long-term effects of the CMCL intervention on HCPs’ social cognitions for discussing leisure-time physical activity (LTPA), and explores key implementation variables that predict changes in HCPs’ social cognitions. Overall Study 2 results suggest that: (1) using a KT framework and integrating stakeholders throughout intervention development increases the likelihood that interventionists will adopt and implement the intervention, and (2) real-world implementation is important to understanding intervention effectiveness. Study 3 examines the effectiveness, and its implementation correlates, of Get in Motion (GIM), a nationwide, LTPA-enhancing telephone counseling service for adults with SCI. Study 3 furthers our understanding of the relationship between implementation and effectiveness, and suggests key implementation ingredients that could be targeted in future refinements of GIM. Together, the dissertation studies contribute to our understanding of how to use theory when developing, implementing, and evaluating behaviour change interventions targeting HCPs and other end-users in the physical disability community. / Dissertation / Doctor of Philosophy (PhD)

Two separate lines of research in object recognition are studies of materials perception and studies of real-world object size perception. Recent object size investigations of texture indicate mid-level features may cue representations of object size in the absence of object identity. However, these findings are somewhat controversial, and beyond that what mid-level features cue object size is not clear. Mid-level features have always been the focus of materials perception studies of gloss and specular highlights, but to date no research has been conducted that attempts to link findings on the perception of materials to high-level object features like real-world object size. Three separate experiments were conducted to study the relationship between perceived surface glossiness and specular highlights, and perceived real-world object size. Previous research on the relationship between perceived object size and real-world object size were replicated. A significant two-way interaction between ratings of perceived glossiness, object size, and texture was found. Follow-up analyses indicated that perceptions of gloss were present across categorical differences in real-world object size in both the object image and texture image task groups. For the normal object images, small objects were perceived as being glossier than big objects. For the texture images, big objects were perceived as being glossier than small objects. Between the conditions, small normal and small texture object images were not significantly different in perceived glossiness. Between the conditions, glossiness ratings for big texture object images were significantly greater than those for the normal big object images. / Doctor of Philosophy / The goal of this project was to understand if category level perceptions of surface gloss (i.e. dull/matte surface reflectance versus shiny/glossy surface reflectance) could predict category level differences in the "actual" size of the objects in the real-world (i.e. small objects versus big objects). Previous research on the relationship between perceived object size and real-world object size were replicated. Moreover, in an experiment in which human subjects were tasked with rating the glossiness of images depicting small and large manmade of objects, category level distinctions in the average perceived glossiness of objects also extended to category level distinctions in perceived real-world object size; on average, small objects were perceived as being glossier than big objects. Similar effects were also found for synthetic textures created from the ordinary real-world object images; on average, big objects were rated as being glossier than small objects. Although categorical distinctions in perceived glossiness extended to real-world object size across image conditions, because there were no significant differences in the average perceived glossiness of small objects across the normal image and texture image conditions, the change in perceived glossiness for the big object images suggests that the texture algorithm used may not have preserved the surface reflectance characteristics of the big objects. Furthermore, statistical investigations of the pixel brightness for the stimulus images provided some evidence that the category level differences in perceived glossiness across object size and image condition may have been driven by differences in factors related to naturally occurring optical artifacts that are introduced when photographing small and big objects. Overall, results of this study are important because they indicate that the real-world spatial properties of objects may be jointly encoded with perceptions of object glossiness.

In nature, many social species demonstrate collective behavior ranging from coordinated motion in flocks of birds and schools of fish to collective decision making in humans. Such distinct behavioral patterns at the group level are the consequence of local interactions among the individuals. We can learn from these biological systems, which have successfully evolved to operate in noisy and fault-prone environments, and understand how these complex interactions can be applied to engineered systems where robustness remains a major challenge. This dissertation addresses a two-scale approach to study these interactions- one in larger scale, where we are interested in the information exchange in a group and how it enables the group to reach a common decision, and the other in a smaller scale, where we are focused in the presence and directionality in the information exchange in a pair of individuals. To understand the interactions at large scale, we use a graph theoretic approach to study consensus or synchronization protocols over two types of biologically-inspired interaction networks. The first network captures both collaborative and antagonistic interactions and the second considers the impact of dynamic leaders in presence of purely collaborative interactions. To study the interactions at small scale, we use an information theoretic approach to understand the directionality of information transfer in a pair of individual using a real-world data-set of animal group motion. Finally, we choose the issue of same-sex marriage in the United States to demonstrate that collective opinion formation is not only a result of negotiations among the individuals, but also reflects inherent spatial and political similarities and temporal delays. / Ph. D. / Social animals exhibit coordination often referred to as ‘collective behavior’ that results from interactions among individuals in the group. This dissertation has demonstrated how interactions can be studied using mathematical modeling, at the same time reveals that real-world interactions are even more complex. Mathematical modeling provides capabilities to introduce biologically inspired phenomena, for example, the implementation of both friendly and hostile interactions that may coexist; and the presence of leader-follower interactions, which is another determinant of collective behavior. The results may find applications in real-world networks, where hostile and leader-follower interactions are prevalent, for example international relations, online social media sites, neural networks, and biologically inspired robotic interactions. We further extend our knowledge regarding interactions by choosing real world systems, the first to understand human decision making, for example in public policies; and the second in animal group motion. Public policy adoption is generally complex and depends on a variety of factors, and no exception is same-sex marriage in the United States which has been a volatile subject for decades until nationwide legalization on June 26, 2015. We target this timely issue and explore the opinion formation of senators and state-law as they evolve over two decades to identify factors that may have affected the dynamics. We unravel geographic proximity, and state-government ideology are significant contributors to the senators opinions and the state-law adoption. Moreover, we build a state-law adoption model which captures these driving factors, and demonstrates predictive power. This study will help to understand or model other public policies that propagate via social and political change. Next we choose the system of bats to investigate navigational leadership roles as they fly in pairs from direct observation of bat swarms in flight. Pairs of bats were continuously tracked in a mountain cave in Shandong Province, China, from which three-dimensional path points are extracted and converted to one-dimensional curvature time series. The study allows us to answer the question of whether individuals fly independently of each other or interact to plan flight paths.

In dieser Dissertation werden Methoden entwickelt, die die Beschreibung der Katalysatoralterung verbessern. Der Fokus liegt hierbei auf der Realalterung in Pkws und Lkws. Die ständig wechselnden Bedingungen im realen Einsatz stellen dabei eine besondere Herausforderung dar. Es wird ein physikalisches Modell entwickelt, das das Wachstum der Edelmetall-Kristallite im Washcoat beschreibt. Anhand der Kristallitgröße wird die katalytische Restaktivität des Katalysators bestimmt. Das Modell kann die Konvertierungsleistung der wesentlichen gasförmigen Schadstoffe CO, HC und sogar NOx berechnen. Es arbeitet vollumfänglich unter stationären thermischen Bedingungen einer Ofenalterung. Weitere Tests könnten es auch zur Anwendung für thermische Realalterung zulassen. Als weitere Methode wird eine empirische Korrelation entwickelt, die die Temperaturbelastung der Katalysatoren kategorisiert und diese damit hinsichtlich ihrer thermischen Realalterung zueinander einordnet. Die thermische Realalterung wird an Diesel-Oxidations-Katalysatoren (DOC) untersucht, die aus einer Edelmetall-Legierung aus Platin und Palladium bestehen. Hinsichtlich der chemischen Realalterung wird eine Diesel-AGN auf ihre Empfindlichkeit gegenüber Ablagerungen und Deaktivierung durch ungerafften Betrieb mit reinem Biodiesel untersucht. Der Biodiesel drängt sich hier in den Fokus, da in diesem, im Vergleich zu fossilem Diesel, deutlich mehr Vergiftungselemente enthalten sein können. / The combustion engine is a very important drive system. An exhaust-aftertreatment system (ATS) is widely mandatory for exhaust-gas purifcation, but the contained catalysts suffer from deactivation by aging effects. To handle the catalyst aging, its description is very significant. This PhD thesis develops two methods to improve the description of thermal real-world aging. The diesel-oxidation-catalyst (DOC) executes crucial conversion-reactions with platinum and palladium as precious metals. They are spread as small particles across the washcoat. Thermal catalyst aging is driven by temperature stress, duration and exhaust-gas atmosphere. It is irreversible and usually the dominating aging-type. Main path of the thermal aging is the precious-metal sintering, at which small precious-metal particles agglomerate to bigger ones. As result the access of the exhaust-gas to the catalyst detoriates, what leads to a deactivation. Chemical catalyst aging originates from negative effect of catalyst poisons and exhibits a very individual behaviour. The developed physical crystallite-size model calculates in its 'base version' the conversion of a catalyst after oven-aging. Input is an arbitrary oven-aging scenario to calculate the resulting crystallite-size and finally to conclude to the catalytic activity. This is possible for every species, thus CO, HC and even NO. Thereby, thermal oven-aging is described by a physical parameter. Furthermore, it is to mention, that the correlation between crystallite size and conversion is explicit for all species. The model is developed at an Pt/Pd-DOC and therefore it is expected, that general catalysts, with and without precious-metal alloys, can be described. The crystallite-size provides also the advantage, that it is independent from chemical aging. So a closed look on thermal aging is possible. The 'base version' of the model can be used in research and development as well for post-mortem analysis. The enhancement of the physical crystallite-size model could allow the description of thermal real-world aging. Input is an inconstant temperature-run for the calculation of the resulting crystallite-size to conclude again to the remaining catalytic activity. A confirmation is not possible with the available data, also the potential of the enhancement cannot be proved. But if the confirmation could get achived, for completely arbitrary thermal real-world aging scenarios the calculation of the conversion for every species would be possible. The field of application would be research and development, on-board operation as well as post-mortem analysis. The developed empirical correlation for real-world aging uses as input inconstant temperatureruns of several DOCs. They are treated by a combination and ranking system. Finally the method outputs a ranking, which represents the remaining catalytic activity. Thereby, the result for the DOCs is qualitative and relative to each other. The available seven real-world aged Pt/Pd-DOCs can get sorted completely correct by the method. The field of application is research and development, on-board operation as well as post-mortem analysis. The chemical real-world aging gets investigated by three ATS, which are driven with DIN EN 14214 biodiesel. Phosphorus and calcium indicate a B100 influence for accumulation. B100 operation clearly causes catalytic deactivation. The activity of the samples at the DOC-outlet correlates with the P+Ca accumulation. But this is not valid for the samples at the DOC-inlet.

Le récit est un outil de communication qui permet aux individus de donner un sens au monde qui les entoure. Il représente une plate-forme pour comprendre et partager leur culture, connaissances et identité. Le récit porte une série d'événements réels ou imaginaires, en provoquant un ressenti, une réaction ou même, déclenche une action. Pour cette raison, il est devenu un sujet d'intérêt pour différents domaines au-delà de la Littérature (Éducation, Marketing, Psychologie, etc.) qui cherchent d'atteindre un but particulier au travers de lui (Persuader, Réfléchir, Apprendre, etc.).Cependant, le récit reste encore sous-développé dans le contexte informatique. Il existent des travaux qui visent son analyse et production automatique. Les algorithmes et implémentations, par contre, restent contraintes à imiter le processus créatif derrière des textes littéraires provenant de sources textuelles. Ainsi, il n'existent pas des approches qui produisent automatiquement des récits dont 1) la source est constitué de matériel non formatées et passé dans la réalité et 2) et le contenu projette une perspective qui cherche à transmettre un message en particulier. Travailler avec des données brutes devient relevante vu qu'elles augmentent exponentiellement chaque jour grâce à l'utilisation d'appareils connectés.Ainsi, vu le contexte du Big Data, nous présentons une approche de génération automatique de récits à partir de données ambiantes. L'objectif est de faire émerger l'expérience vécue d'une personne à partir des données produites pendant une activité humaine. Tous les domaines qui travaillent avec des données brutes pourraient bénéficier de ce travail, tels que l'Éducation ou la Santé. Il s'agit d'un effort interdisciplinaire qui inclut le Traitement Automatique de Langues, la Narratologie, les Sciences Cognitives et l'Interaction Homme-Machine.Cette approche est basée sur des corpus et modèles et comprend la formalisation de ce que nous appelons le récit d'activité ainsi qu'une démarche de génération adaptée. Elle a est composé de 4 étapes : la formalisation des récits d'activité, la constitution de corpus, la construction de modèles d'activité et du récit, et la génération de texte. Chacune a été conçue pour surmonter des contraintes liées aux questions scientifiques posées vue la nature de l'objectif : la manipulation de données incertaines et incomplètes, l'abstraction valide d'après l'activité, la construction de modèles avec lesquels il soit possible la transposition de la réalité gardée dans les données vers une perspective subjective et la rendue en langage naturel. Nous avons utilisé comme cas d'usage le récit d'activité, vu que les pratiquant se servent des appareils connectés, ainsi qu'ils ont besoin de partager son expérience. Les résultats obtenus sont encourageants et donnent des pistes qui ouvrent beaucoup de perspectives de recherche. / Stories are a communication tool that allow people to make sense of the world around them. It represents a platform to understand and share their culture, knowledge and identity. Stories carry a series of real or imaginary events, causing a feeling, a reaction or even trigger an action. For this reason, it has become a subject of interest for different fields beyond Literature (Education, Marketing, Psychology, etc.) that seek to achieve a particular goal through it (Persuade, Reflect, Learn, etc.).However, stories remain underdeveloped in Computer Science. There are works that focus on its analysis and automatic production. However, those algorithms and implementations remain constrained to imitate the creative process behind literary texts from textual sources. Thus, there are no approaches that produce automatically stories whose 1) the source consists of raw material that passed in real life and 2) and the content projects a perspective that seeks to convey a particular message. Working with raw data becomes relevant today as it increase exponentially each day through the use of connected devices.Given the context of Big Data, we present an approach to automatically generate stories from ambient data. The objective of this work is to bring out the lived experience of a person from the data produced during a human activity. Any areas that use such raw data could benefit from this work, for example, Education or Health. It is an interdisciplinary effort that includes Automatic Language Processing, Narratology, Cognitive Science and Human-Computer Interaction.This approach is based on corpora and models and includes the formalization of what we call the activity récit as well as an adapted generation approach. It consists of 4 stages: the formalization of the activity récit, corpus constitution, construction of models of activity and the récit, and the generation of text. Each one has been designed to overcome constraints related to the scientific questions asked in view of the nature of the objective: manipulation of uncertain and incomplete data, valid abstraction according to the activity, construction of models from which it is possible the Transposition of the reality collected though the data to a subjective perspective and rendered in natural language. We used the activity narrative as a case study, as practitioners use connected devices, so they need to share their experience. The results obtained are encouraging and give leads that open up many prospects for research.

A relatively large number of 8th-grade public middle school students in the United States, particularly in urban communities, are not performing at acceptable levels in mathematics. One concept that poses significant difficulty for these students and negatively affects their overall mathematics achievement is fractions. Many researchers have attributed these difficulties primarily to traditional fraction instruction that emphasizes procedural rather than conceptual knowledge. Therefore this study was designed to investigate how students use their computational and conceptual knowledge and fraction representations to solve fraction-related performance-based mathematical tasks. Social constructivism was used as the theoretical framework in examining conceptual knowledge related to learning fractions. This qualitative study was implemented in an urban middle school in the southeast. It involved an initial sample of 37, 8th-grade, African American pre-algebra students who completed a fraction interest questionnaire and two fraction pretests. During the implementation period, 34 students in the researcher’s pre-algebra class completed three performance-based tasks, three reflection logs, and participated in an interview after completing each task. Of the 34 students who completed all tasks, three were purposefully selected as the informants for the study. In addition, observations, field notes, and artifacts (student work) were utilized to facilitate triangulation of the data. The findings of the study indicated the informants could compute fractions with an average of 85% of mastery but could conceptualize fractions only to a small extent. This validated prior findings and led to the conclusion that student deficiency with fractions results primarily from their level of conceptual knowledge. In the investigation of the ways in which 8th-grade students use fraction representations, this study found the informants used representations to develop a visual map of their mathematical thinking and reasoning and to check the accuracy of their computations. Therefore, this study suggests, when students’ mathematical learning experiences relative to fractions have not emphasized the use of representations to develop conceptual knowledge, they may not be comfortable with the accuracy of the solutions demonstrated in their fractions models.

Darbe pateikiamas naujas lokaliojo koliažo principu grįstas fraktalinių interpoliacinių funkcijų generavimo algoritmas (procedūra) su pilna kompiuterine realizacija. Siūlomas įrankis orientuotas į realaus pasaulio objektų (sistem��), pasižyminčių "atsikartojimu savyje" (fraktališkumu), modeliavimą. Atlikti preliminarūs eksperimentai patvirtina metodo perspektyvumą. / In the paper, a new method (tool) for the generation of fractal interpolation functions is presented. The proposed interpolation tool is oriented to process data arrays having links with real-world objects. The interpolation process itself explores self-similiarities found within data arrays under processing, as well as exciting properties of the local collage theorem. Some preliminary experimental results are presented.