The Learning Affect Monitor (LAM) - A computer-based system integrating quantitative and qualitative assessment of affective states in daily life.

The Learning Affect Monitor (LAM) is a new computer-based assessment system integrating basic dimensional evaluation and discrete description of affective states in daily life, based on an autonomous adapting system. Subjects evaluate their affective states according to a tridimensional space (valence and activation circumplex as well as global intensity) and then qualify it using up to 30 adjective descriptors chosen from a list. The system gradually adapts to the user, enabling the affect descriptors it presents to be increasingly relevant. An initial study with 51 subjects, using a 1 week time-sampling with 8 to 10 randomized signals per day, produced n = 2,813 records with good reliability measures (e.g., response rate of 88.8%, mean split-half reliability of .86), user acceptance, and usability. Multilevel analyses show circadian and hebdomadal patterns, and significant individual and situational variance components of the basic dimension evaluations. Validity analyses indicate sound assignment of qualitative affect descriptors in the bidimensional semantic space according to the circumplex model of basic affect dimensions. The LAM assessment module can be implemented on different platforms (palm, desk, mobile phone) and provides very rapid and meaningful data collection, preserving complex and interindividually comparable information in the domain of emotion and well-being.

Virological and Immunological Characterization of Novel NYVAC-Based HIV/AIDS Vaccine Candidates Expressing Clade C Trimeric Soluble gp140(ZM96) and Gag(ZM96)-Pol-Nef(CN54) as Virus-Like Particles.

The generation of vaccines against HIV/AIDS able to induce long-lasting protective immunity remains a major goal in the HIV field. The modest efficacy (31.2%) against HIV infection observed in the RV144 phase III clinical trial highlighted the need for further improvement of HIV vaccine candidates, formulation, and vaccine regimen. In this study, we have generated two novel NYVAC vectors, expressing HIV-1 clade C gp140(ZM96) (NYVAC-gp140) or Gag(ZM96)-Pol-Nef(CN54) (NYVAC-Gag-Pol-Nef), and defined their virological and immunological characteristics in cultured cells and in mice. The insertion of HIV genes does not affect the replication capacity of NYVAC recombinants in primary chicken embryo fibroblast cells, HIV sequences remain stable after multiple passages, and HIV antigens are correctly expressed and released from cells, with Env as a trimer (NYVAC-gp140), while in NYVAC-Gag-Pol-Nef-infected cells Gag-induced virus-like particles (VLPs) are abundant. Electron microscopy revealed that VLPs accumulated with time at the cell surface, with no interference with NYVAC morphogenesis. Both vectors trigger specific innate responses in human cells and show an attenuation profile in immunocompromised adult BALB/c and newborn CD1 mice after intracranial inoculation. Analysis of the immune responses elicited in mice after homologous NYVAC prime/NYVAC boost immunization shows that recombinant viruses induced polyfunctional Env-specific CD4 or Gag-specific CD8 T cell responses. Antibody responses against gp140 and p17/p24 were elicited. Our findings showed important insights into virus-host cell interactions of NYVAC vectors expressing HIV antigens, with the activation of specific immune parameters which will help to unravel potential correlates of protection against HIV in human clinical trials with these vectors. IMPORTANCE: We have generated two novel NYVAC-based HIV vaccine candidates expressing HIV-1 clade C trimeric soluble gp140 (ZM96) and Gag(ZM96)-Pol-Nef(CN54) as VLPs. These vectors are stable and express high levels of both HIV-1 antigens. Gag-induced VLPs do not interfere with NYVAC morphogenesis, are highly attenuated in immunocompromised and newborn mice after intracranial inoculation, trigger specific innate immune responses in human cells, and activate T (Env-specific CD4 and Gag-specific CD8) and B cell immune responses to the HIV antigens, leading to high antibody titers against gp140. For these reasons, these vectors can be considered vaccine candidates against HIV/AIDS and currently are being tested in macaques and humans.

A design science approach to support the assessment of disruptive technology : the Swiss mobile payment case

Abstract In this thesis we present the design of a systematic integrated computer-based approach for detecting potential disruptions from an industry perspective. Following the design science paradigm, we iteratively develop several multi-actor multi-criteria artifacts dedicated to environment scanning. The contributions of this thesis are both theoretical and practical. We demonstrate the successful use of multi-criteria decision-making methods for technology foresight. Furthermore, we illustrate the design of our artifacts using build and-evaluate loops supported with a field study of the Swiss mobile payment industry. To increase the relevance of this study, we systematically interview key Swiss experts for each design iteration. As a result, our research provides a realistic picture of the current situation in the Swiss mobile payment market and reveals previously undiscovered weak signals for future trends. Finally, we suggest a generic design process for environment scanning.

Evaluation of an online, case-based interactive approach to teaching pathophysiology

AIM: The aim of this study was to evaluate a new pedagogical approach in teaching fluid, electrolyte and acid-base pathophysiology in undergraduate students. METHODS: This approach comprises traditional lectures, the study of clinical cases on the web and a final interactive discussion of these cases in the classroom. When on the web, the students are asked to select laboratory tests that seem most appropriate to understand the pathophysiological condition underlying the clinical case. The percentage of students having chosen a given test is made available to the teacher who uses it in an interactive session to stimulate discussion with the whole class of students. The same teacher used the same case studies during 2 consecutive years during the third year of the curriculum. RESULTS: The majority of students answered the questions on the web as requested and evaluated positively their experience with this form of teaching and learning. CONCLUSIONS: Complementing traditional lectures with online case-based studies and interactive group discussions represents, therefore, a simple means to promote the learning and the understanding of complex pathophysiological mechanisms. This simple problem-based approach to teaching and learning may be implemented to cover all fields of medicine.

L'informatique: un outil remarquable pour l'enseignement de la médecine interne générale [The informatics: a remarkable tool for teaching general internal medicine].

INTERMED training implies a three week course, integrated in the "primary care module" for medical students in the first master year at the school of medicine in Lausanne. INTERMED uses an innovative teaching method based on repetitive sequences of e-learning-based individual learning followed by collaborative learning activities in teams, named Team-based learning (TBL). The e-learning takes place in a web-based virtual learning environment using a series of interactive multimedia virtual patients. By using INTERMED students go through a complete medical encounter applying clinical reasoning and choosing the diagnostic and therapeutic approach. INTERMED offers an authentic experience in an engaging and safe environment where errors are allowed and without consequences.

Evolution of decision-making and learning under fluctuating social environments

The capacity to learn to associate sensory perceptions with appropriate motor actions underlies the success of many animal species, from insects to humans. The evolutionary significance of learning has long been a subject of interest for evolutionary biologists who emphasize the bene¬fit yielded by learning under changing environmental conditions, where it is required to flexibly switch from one behavior to another. However, two unsolved questions are particularly impor¬tant for improving our knowledge of the evolutionary advantages provided by learning, and are addressed in the present work. First, because it is possible to learn the wrong behavior when a task is too complex, the learning rules and their underlying psychological characteristics that generate truly adaptive behavior must be identified with greater precision, and must be linked to the specific ecological problems faced by each species. A framework for predicting behavior from the definition of a learning rule is developed here. Learning rules capture cognitive features such as the tendency to explore, or the ability to infer rewards associated to unchosen actions. It is shown that these features interact in a non-intuitive way to generate adaptive behavior in social interactions where individuals affect each other's fitness. Such behavioral predictions are used in an evolutionary model to demonstrate that, surprisingly, simple trial-and-error learn¬ing is not always outcompeted by more computationally demanding inference-based learning, when population members interact in pairwise social interactions. A second question in the evolution of learning is its link with and relative advantage compared to other simpler forms of phenotypic plasticity. After providing a conceptual clarification on the distinction between genetically determined vs. learned responses to environmental stimuli, a new factor in the evo¬lution of learning is proposed: environmental complexity. A simple mathematical model shows that a measure of environmental complexity, the number of possible stimuli in one's environ¬ment, is critical for the evolution of learning. In conclusion, this work opens roads for modeling interactions between evolving species and their environment in order to predict how natural se¬lection shapes animals' cognitive abilities. - La capacité d'apprendre à associer des sensations perceptives à des actions motrices appropriées est sous-jacente au succès évolutif de nombreuses espèces, depuis les insectes jusqu'aux êtres hu¬mains. L'importance évolutive de l'apprentissage est depuis longtemps un sujet d'intérêt pour les biologistes de l'évolution, et ces derniers mettent l'accent sur le bénéfice de l'apprentissage lorsque les conditions environnementales sont changeantes, car dans ce cas il est nécessaire de passer de manière flexible d'un comportement à l'autre. Cependant, deux questions non résolues sont importantes afin d'améliorer notre savoir quant aux avantages évolutifs procurés par l'apprentissage. Premièrement, puisqu'il est possible d'apprendre un comportement incorrect quand une tâche est trop complexe, les règles d'apprentissage qui permettent d'atteindre un com¬portement réellement adaptatif doivent être identifiées avec une plus grande précision, et doivent être mises en relation avec les problèmes écologiques spécifiques rencontrés par chaque espèce. Un cadre théorique ayant pour but de prédire le comportement à partir de la définition d'une règle d'apprentissage est développé ici. Il est démontré que les caractéristiques cognitives, telles que la tendance à explorer ou la capacité d'inférer les récompenses liées à des actions non ex¬périmentées, interagissent de manière non-intuitive dans les interactions sociales pour produire des comportements adaptatifs. Ces prédictions comportementales sont utilisées dans un modèle évolutif afin de démontrer que, de manière surprenante, l'apprentissage simple par essai-et-erreur n'est pas toujours battu par l'apprentissage basé sur l'inférence qui est pourtant plus exigeant en puissance de calcul, lorsque les membres d'une population interagissent socialement par pair. Une deuxième question quant à l'évolution de l'apprentissage concerne son lien et son avantage relatif vis-à-vis d'autres formes plus simples de plasticité phénotypique. Après avoir clarifié la distinction entre réponses aux stimuli génétiquement déterminées ou apprises, un nouveau fac¬teur favorisant l'évolution de l'apprentissage est proposé : la complexité environnementale. Un modèle mathématique permet de montrer qu'une mesure de la complexité environnementale - le nombre de stimuli rencontrés dans l'environnement - a un rôle fondamental pour l'évolution de l'apprentissage. En conclusion, ce travail ouvre de nombreuses perspectives quant à la mo¬délisation des interactions entre les espèces en évolution et leur environnement, dans le but de comprendre comment la sélection naturelle façonne les capacités cognitives des animaux.

A new neuropsychological instrument measuring effects of age and drugs on fitness to drive: development, reliability, and validity of MedDrive

Background: Current guidelines underline the limitations of existing instruments to assess fitness to drive and the poor adaptability of batteries of neuropsychological tests in primary care settings. Aims: To provide a free, reliable, transparent computer based instrument capable of detecting effects of age or drugs on visual processing and cognitive functions. Methods: Relying on systematic reviews of neuropsychological tests and driving performances, we conceived four new computed tasks measuring: visual processing (Task1), movement attention shift (Task2), executive response, alerting and orientation gain (Task3), and spatial memory (Task4). We then planned five studies to test MedDrive's reliability and validity. Study-1 defined instructions and learning functions collecting data from 105 senior drivers attending an automobile club course. Study-2 assessed concurrent validity for detecting minor cognitive impairment (MCI) against useful field of view (UFOV) on 120 new senior drivers. Study-3 collected data from 200 healthy drivers aged 20-90 to model age related normal cognitive decline. Study-4 measured MedDrive's reliability having 21 healthy volunteers repeat tests five times. Study-5 tested MedDrive's responsiveness to alcohol in a randomised, double-blinded, placebo, crossover, dose-response validation trial including 20 young healthy volunteers. Results: Instructions were well understood and accepted by all senior drivers. Measures of visual processing (Task1) showed better performances than the UFOV in detecting MCI (ROC 0.770 vs. 0.620; p=0.048). MedDrive was capable of explaining 43.4% of changes occurring with natural cognitive decline. In young healthy drivers, learning effects became negligible from the third session onwards for all tasks except for dual tasking (ICC=0.769). All measures except alerting and orientation gain were affected by blood alcohol concentrations. Finally, MedDrive was able to explain 29.3% of potential causes of swerving on the driving simulator. Discussion and conclusions: MedDrive reveals improved performances compared to existing computed neuropsychological tasks. It shows promising results both for clinical and research purposes.

Automatic classification of MR scans in Alzheimer's disease.

To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.

Teaching evidence-based management with a focus on producing local evidence

We present an approach to teaching evidence-based management (EBMgt) that trains future managers how to produce local evidence. Local evidence is causally interpretable data, collected on-site in companies to address a specific business problem. Our teaching method is a variant of problem-based learning, a method originally developed to teach evidence-based medicine. Following this method, students learn an evidence-based problem-solving cycle for addressing actual business cases. Executing this cycle, students use and produce scientific evidence through literature searches and the design of local, experimental tests of causal hypotheses. We argue the value of teaching EBMgt with a focus on producing local evidence, how it can be taught, and what can be taught. We conclude by outlining our contribution to the literature on teaching EBMgt and by discussing limitations of our approach.

LEVERAGING SANDBOX IMMERSIVE 3D VIRTUAL WORLDS TO DEVELOP DO-IT- YOURSELF TEACHING GAMES: IMPLEMENTATION TO MARKETING CASE STUDY TEACHING IN SECOND LIFE

Games are powerful and engaging. On average, one billion people spend at least 1 hour a day playing computer and videogames. This is even more true with the younger generations. Our students have become the < digital natives >, the < gamers >, the < virtual generation >. Research shows that those who are most at risk for failure in the traditional classroom setting, also spend more time than their counterparts, using video games. They might strive, given a different learning environment. Educators have the responsibility to align their teaching style to these younger generation learning styles. However, many academics resist the use of computer-assisted learning that has been "created elsewhere". This can be extrapolated to game-based teaching: even if educational games were more widely authored, their adoption would still be limited to the educators who feel a match between the authored games and their own beliefs and practices. Consequently, game-based teaching would be much more widespread if teachers could develop their own games, or at least customize them. Yet, the development and customization of teaching games are complex and costly. This research uses a design science methodology, leveraging gamification techniques, active and cooperative learning theories, as well as immersive sandbox 3D virtual worlds, to develop a method which allows management instructors to transform any off-the-shelf case study into an engaging collaborative gamified experience. This method is applied to marketing case studies, and uses the sandbox virtual world of Second Life. -- Les jeux sont puissants et motivants, En moyenne, un milliard de personnes passent au moins 1 heure par jour jouer à des jeux vidéo sur ordinateur. Ceci se vérifie encore plus avec les jeunes générations, Nos étudiants sont nés à l'ère du numérique, certains les appellent des < gamers >, d'autres la < génération virtuelle >. Les études montrent que les élèves qui se trouvent en échec scolaire dans les salles de classes traditionnelles, passent aussi plus de temps que leurs homologues à jouer à des jeux vidéo. lls pourraient potentiellement briller, si on leur proposait un autre environnement d'apprentissage. Les enseignants ont la responsabilité d'adapter leur style d'enseignement aux styles d'apprentissage de ces jeunes générations. Toutefois, de nombreux professeurs résistent lorsqu'il s'agit d'utiliser des contenus d'apprentissage assisté par ordinateur, développés par d'autres. Ceci peut être extrapolé à l'enseignement par les jeux : même si un plus grand nombre de jeux éducatifs était créé, leur adoption se limiterait tout de même aux éducateurs qui perçoivent une bonne adéquation entre ces jeux et leurs propres convictions et pratiques. Par conséquent, I'enseignement par les jeux serait bien plus répandu si les enseignants pouvaient développer leurs propres jeux, ou au moins les customiser. Mais le développement de jeux pédagogiques est complexe et coûteux. Cette recherche utilise une méthodologie Design Science pour développer, en s'appuyant sur des techniques de ludification, sur les théories de pédagogie active et d'apprentissage coopératif, ainsi que sur les mondes virtuels immersifs < bac à sable > en 3D, une méthode qui permet aux enseignants et formateurs de management, de transformer n'importe quelle étude de cas, provenant par exemple d'une centrale de cas, en une expérience ludique, collaborative et motivante. Cette méthode est appliquée aux études de cas Marketing dans le monde virtuel de Second Life.

Beyond the 'dyad': a qualitative re-evaluation of the changing clinical consultation.

OBJECTIVE: To identify characteristics of consultations that do not conform to the traditionally understood communication 'dyad', in order to highlight implications for medical education and develop a reflective 'toolkit' for use by medical practitioners and educators in the analysis of consultations. DESIGN: A series of interdisciplinary research workshops spanning 12 months explored the social impact of globalisation and computerisation on the clinical consultation, focusing specifically on contemporary challenges to the clinician-patient dyad. Researchers presented detailed case studies of consultations, taken from their recent research projects. Drawing on concepts from applied sociolinguistics, further analysis of selected case studies prompted the identification of key emergent themes. SETTING: University departments in the UK and Switzerland. PARTICIPANTS: Six researchers with backgrounds in medicine, applied linguistics, sociolinguistics and medical education. One workshop was also attended by PhD students conducting research on healthcare interactions. RESULTS: The contemporary consultation is characterised by a multiplicity of voices. Incorporation of additional voices in the consultation creates new forms of order (and disorder) in the interaction. The roles 'clinician' and 'patient' are blurred as they become increasingly distributed between different participants. These new consultation arrangements make new demands on clinicians, which lie beyond the scope of most educational programmes for clinical communication. CONCLUSIONS: The consultation is changing. Traditional consultation models that assume a 'dyadic' consultation do not adequately incorporate the realities of many contemporary consultations. A paradox emerges between the need to manage consultations in a 'super-diverse' multilingual society, while also attending to increasing requirements for standardised protocol-driven approaches to care prompted by computer use. The tension between standardisation and flexibility requires addressing in educational contexts. Drawing on concepts from applied sociolinguistics and the findings of these research observations, the authors offer a reflective 'toolkit' of questions to ask of the consultation in the context of enquiry-based learning.

The establishment of communication systems depends on the scale of competition

How communication systems emerge and remain stable is an important question in both cognitive science and evolutionary biology. For communication to arise, not only must individuals cooperate by signaling reliable information, but they must also coordinate and perpetuate signals. Most studies on the emergence of communication in humans typically consider scenarios where individuals implicitly share the same interests. Likewise, most studies on human cooperation consider scenarios where shared conventions of signals and meanings cannot be developed de novo. Here, we combined both approaches with an economic experiment where participants could develop a common language, but under different conditions fostering or hindering cooperation. Participants endeavored to acquire a resource through a learning task in a computer-based environment. After this task, participants had the option to transmit a signal (a color) to a fellow group member, who would subsequently play the same learning task. We varied the way participants competed with each other (either global scale or local scale) and the cost of transmitting a signal (either costly or noncostly) and tracked the way in which signals were used as communication among players. Under global competition, players signaled more often and more consistently, scored higher individual payoffs, and established shared associations of signals and meanings. In addition, costly signals were also more likely to be used under global competition; whereas under local competition, fewer signals were sent and no effective communication system was developed. Our results demonstrate that communication involves both a coordination and a cooperative dilemma and show the importance of studying language evolution under different conditions influencing human cooperation.