Efficacy of prescribed injectable diacetylmorphine in the Andalusian trial: Bayesian analysis of responders and non-responders according to a multi domain outcome index.

BACKGROUND The objective of this research was to evaluate data from a randomized clinical trial that tested injectable diacetylmorphine (DAM) and oral methadone (MMT) for substitution treatment, using a multi-domain dichotomous index, with a Bayesian approach. METHODS Sixty two long-term, socially-excluded heroin injectors, not benefiting from available treatments were randomized to receive either DAM or MMT for 9 months in Granada, Spain. Completers were 44 and data at the end of the study period was obtained for 50. Participants were determined to be responders or non responders using a multi-domain outcome index accounting for their physical and mental health and psychosocial integration, used in a previous trial. Data was analyzed with Bayesian methods, using information from a similar study conducted in The Netherlands to select a priori distributions. On adding the data from the present study to update the a priori information, the distribution of the difference in response rates were obtained and used to build credibility intervals and relevant probability computations. RESULTS In the experimental group (n = 27), the rate of responders to treatment was 70.4% (95% CI 53.287.6), and in the control group (n = 23), it was 34.8% (95% CI 15.354.3). The probability of success in the experimental group using the a posteriori distributions was higher after a proper sensitivity analysis. Almost the whole distribution of the rates difference (the one for diacetylmorphine minus methadone) was located to the right of the zero, indicating the superiority of the experimental treatment. CONCLUSION The present analysis suggests a clinical superiority of injectable diacetylmorphine compared to oral methadone in the treatment of severely affected heroin injectors not benefiting sufficiently from the available treatments. TRIAL REGISTRATION Current Controlled Trials ISRCTN52023186.

Two-sided learning in new keynesian models: dynamics, (lack of) convergence and the value of information

This paper investigates the role of learning by private agents and the central bank (two-sided learning) in a New Keynesian framework in which both sides of the economy have asymmetric and imperfect knowledge about the true data generating process. We assume that all agents employ the data that they observe (which may be distinct for different sets of agents) to form beliefs about unknown aspects of the true model of the economy, use their beliefs to decide on actions, and revise these beliefs through a statistical learning algorithm as new information becomes available. We study the short-run dynamics of our model and derive its policy recommendations, particularly with respect to central bank communications. We demonstrate that two-sided learning can generate substantial increases in volatility and persistence, and alter the behavior of the variables in the model in a signifficant way. Our simulations do not converge to a symmetric rational expectations equilibrium and we highlight one source that invalidates the convergence results of Marcet and Sargent (1989). Finally, we identify a novel aspect of central bank communication in models of learning: communication can be harmful if the central bank's model is substantially mis-specified

Understanding the development of the ESDP: Perspectives and insights from historical institutionalism and theories of learning

How can we best understand the emergence of the European Security and Defence Policy (ESDP)? This paper applies the theories of historical institutionalism and experiential learning to offer a dynamic conceptualisation of moves towards an ESDP which highlights some of the causal factors that a more temporally-restricted analysis would miss. It firstly shows how the institutional and functional expansion of European Political Cooperation (EPC) over the course of the 1970s and 80s gave rise to a context in which the development of a security and defence dimension came to be viewed as more logical and even necessary. It then goes on to analyse some of the external factors (in the form of actors, events and institutions) that further pushed in this direction and proved to influence the policy’s subsequent evolution. The paper is therefore intended to act as a first-step to understanding the ESDP’s development from this perspective.

A Formal Framework for Specifying, Reusing and Implementing Learning Processes. First level

This file contains the ontology of patterns of educational settings, as part of the formal framework for specifying, reusing and implementing educational settings. Furthermore, it includes the set of rules that extend the ontology of educational scenarios as well as a brief description of the level of patters of such ontological framework.

Reduced learning ability as a consequence of evolutionary adaptation to nutritional stress in Drosophila melanogaster

1. Dietary conditions affect cognitive abilities of many species, but it is unclear to what extent this physiological effect translates into an evolutionary relationship. 2. A reduction of competitive ability under nutritional stress has been reported as a correlated response to selection for learning ability in Drosophila melanogaster. Here we test whether the reverse holds as well, i.e. whether an evolutionary adaptation to poor food conditions leads to a decrease in learning capacities. 3. Populations of D. melanogaster were: (i) not subject to selection (control), (ii) selected for improved learning ability, (iii) selected for survival and fast development on poor food, or (iv) subject to both selection regimes. 4. There was no detectable response to selection for learning ability. 5. Selection on poor food led to higher survival, faster development and smaller adult size as a direct response, and to reduced learning ability as a correlated response. This study supports the hypothesis that adaptation to poor nutrition is likely to trade off with the evolution of improved learning ability.

On optimal learning schedules and the marginal value of cumulative cultural evolution.

The age-dependent choice between expressing individual learning (IL) or social learning (SL) affects cumulative cultural evolution. A learning schedule in which SL precedes IL is supportive of cumulative culture because the amount of nongenetically encoded adaptive information acquired by previous generations can be absorbed by an individual and augmented. Devoting time and energy to learning, however, reduces the resources available for other life-history components. Learning schedules and life history thus coevolve. Here, we analyze a model where individuals may have up to three distinct life stages: "infants" using IL or oblique SL, "juveniles" implementing IL or horizontal SL, and adults obtaining material resources with learned information. We study the dynamic allocation of IL and SL within life stages and how this coevolves with the length of the learning stages. Although no learning may be evolutionary stable, we find conditions where cumulative cultural evolution can be selected for. In that case, the evolutionary stable learning schedule causes individuals to use oblique SL during infancy and a mixture between IL and horizontal SL when juvenile. We also find that the selected pattern of oblique SL increases the amount of information in the population, but horizontal SL does not do so.

Curriculum sequencing for an e-learning system based on learning styles

This work shows the use of adaptation techniques involved in an e-learning system that considers students' learning styles and students' knowledge states. The mentioned e-learning system is built on a multiagent framework designed to examine opportunities to improve the teaching and to motivate the students to learn what they want in a user-friendly and assisted environment

Engaging students in an e-learning experience : how to manage information resources through wikis and web blogs

The purpose of this paper is to describe the collaboration between librarians and scholars, from a virtual university, in order to facilitate collaborative learning on how to manage information resources. The personal information behaviour of e-learning students when managing information resources for academic, professional and daily life purposes was studied from 24 semi-structured face-to-face interviews. The results of the content analysis of the interview' transcriptions, highlighted that in the workplace and daily life contexts, competent information behaviour is always linked to a proactive attitude, that is to say, that participants seek for information without some extrinsic reward or avoiding punishment. In the academic context, it was observed a low level of information literacy and it seems to be related with a prevalent uninvolved attitude.

Train-the-trainer: E-learning zur Förderung einer praxisorientiertem Vermittlung von evidenzbasierter Medizin

Hintergrund: Trotz ihrer Etablierung als essentieller Bestandteil der medizinischen Weiter-/Fortbildung werden europa- wie schweizweit kaum Kurse in evidenzbasierter Medizin (ebm) angeboten, die - integriert im klinischen Alltag - gezielt Fertigkeiten in ebm vermitteln. Noch grössere Defizite finden sich bei ebm- Weiterbildungsmöglichkeiten für klinische Ausbilder (z.B. Oberärzte). Als Weiterführung eines EU-finanzierten, klinisch integrierten E-learning- Programms für Weiterbildungsassistenten (www.ebm-unity.org) entwickelte eine europäische Gruppe von medical educators gezielt für Ausbilder ein e-learning-Curriculum zur Vermittlung von ebm im Rahmen der klinischen Weiterbildung. Methode: Die Entwicklung des Curriculums umfasst folgende Schritte: Beschreibung von Lernzielen, Identifikation von klinisch relevanten Lernumgebungen, Entwicklung von Lerninhalten und exemplarischen didaktischen Strategien, zugeschnitten auf die jeweilige Lernumgebungen, Design von web-basierten Selbst-Lernsequenzen mit Möglichkeiten zur Selbstevaluation, Erstellung eines Handbuchs. Ergebnisse: Lernziele des Tutoren-Lehrgangs sind der Erwerb von Fertigkeiten zur Vermittlung der 5 klassischen ebm-Schritte: PICO- (Patient-Intervention-Comparison-Outcome)-Fragen, Literatursuche, kritische Literaturbewertung, Übertragung der Ergebnisse im eigenen Setting und Implementierung). Die Lehrbeispiele zeigen angehenden ebm-Tutoren, wie sich typische klinische Situationen wie z.B. Stationsvisite, Ambulanzsprechstunde, Journalclub, offizielle Konferenzen, Audit oder das klinische Assessment von Weiterbildungsassistenten gezielt für die Vermittlung von ebm nutzen lassen. Kurze E-Learning-Module mit exemplarischen «real-life»-Video-Clips erlauben flexibles Lernen zugeschnitten auf das knappe Zeitkontingent von Ärzten. Eine Selbst-Evaluation ermöglicht die Überprüfung der gelernten Inhalte. Die Pilotierung des Tutoren-Lehrgangs mit klinisch tätigen Tutoren sowie die Übersetzung des Moduls in weitere Sprachen sind derzeit in Vorbereitung. chlussfolgerung: Der modulare Train-the-Trainer-Kurs zur Vermittlung von ebm im klinischen Alltag schliesst eine wichtige Lücke in der Dissemination von klinischer ebm. Webbasierte Beispiele mit kurzen Sequenzen demonstrieren typische Situationen zur Vermittlung der ebm-Kernfertigkeiten und bieten medical educators wie Oberärzten einen niedrigschwelligen Einstieg in «ebm» am Krankenbett. Langfristiges Ziel ist eine europäische Qualifikation für ebm- Learning und -Teaching in der Fort- und Weiterbildung. Nach Abschluss der Evaluation steht das Curriculum interessierten Personen und Gruppen unter «not-for-profit»-Bedingungen zur Verfügung. Auskünfte erhältlich von rkunz@uhbs.ch. Finanziert durch die Europäische Kommission - Leonardo da Vinci Programme - Transfer of Innovation - Pilot Project for Lifelong Learn- ing 2007 und das Schweizerische Staatssekretariat für Bildung und Forschung.

Bayesian nash equilibrium in ''linear'' cournot models with private information about costs

Calculating explicit closed form solutions of Cournot models where firms have private information about their costs is, in general, very cumbersome. Most authors consider therefore linear demands and constant marginal costs. However, within this framework, the nonnegativity constraint on prices (and quantities) has been ignored or not properly dealt with and the correct calculation of all Bayesian Nash equilibria is more complicated than expected. Moreover, multiple symmetric and interior Bayesianf equilibria may exist for an open set of parameters. The reason for this is that linear demand is not really linear, since there is a kink at zero price: the general ''linear'' inverse demand function is P (Q) = max{a - bQ, 0} rather than P (Q) = a - bQ.

Bayesian Markov chain Monte Carlo inversion of geophysical data for the purpose of estimating the hydraulic properties of the unsaturated zone

Ground-penetrating radar (GPR) has the potential to provide valuable information on hydrological properties of the vadose zone because of their strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR data within a coupled geophysical-hydrological framework may allow for effective estimation of subsurface van-Genuchten-Mualem (VGM) parameters and their corresponding uncertainties. An important and still unresolved issue, however, is how to best integrate GPR data into a stochastic inversion in order to estimate the VGM parameters and their uncertainties, thus improving hydrological predictions. Recognizing the importance of this issue, the aim of the research presented in this thesis was to first introduce a fully Bayesian inversion called Markov-chain-Monte-carlo (MCMC) strategy to perform the stochastic inversion of steady-state GPR data to estimate the VGM parameters and their uncertainties. Within this study, the choice of the prior parameter probability distributions from which potential model configurations are drawn and tested against observed data was also investigated. Analysis of both synthetic and field data collected at the Eggborough (UK) site indicates that the geophysical data alone contain valuable information regarding the VGM parameters. However, significantly better results are obtained when these data are combined with a realistic, informative prior. A subsequent study explore in detail the dynamic infiltration case, specifically to what extent time-lapse ZOP GPR data, collected during a forced infiltration experiment at the Arrenaes field site (Denmark), can help to quantify VGM parameters and their uncertainties using the MCMC inversion strategy. The findings indicate that the stochastic inversion of time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions. In turn, this significantly improves knowledge of the hydraulic properties, which are required to predict hydraulic behaviour. Finally, another aspect that needed to be addressed involved the comparison of time-lapse GPR data collected under different infiltration conditions (i.e., natural loading and forced infiltration conditions) to estimate the VGM parameters using the MCMC inversion strategy. The results show that for the synthetic example, considering data collected during a forced infiltration test helps to better refine soil hydraulic properties compared to data collected under natural infiltration conditions. When investigating data collected at the Arrenaes field site, further complications arised due to model error and showed the importance of also including a rigorous analysis of the propagation of model error with time and depth when considering time-lapse data. Although the efforts in this thesis were focused on GPR data, the corresponding findings are likely to have general applicability to other types of geophysical data and field environments. Moreover, the obtained results allow to have confidence for future developments in integration of geophysical data with stochastic inversions to improve the characterization of the unsaturated zone but also reveal important issues linked with stochastic inversions, namely model errors, that should definitely be addressed in future research.

Cap a una definició inclusiva de l'e-learning

Peer-reviewed

Learning spatial filters for multispectral image segmentation

We present a novel filtering method for multispectral satellite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments carried out on multiclass one-against-all classification and target detection show the capabilities of the learned spatial filters.

Adaption of Courses and Learning Environment to the User Context in dotLRN

The explosive growth of Internet during the last years has been reflected in the ever-increasing amount of the diversity and heterogeneity of user preferences, types and features of devices and access networks. Usually the heterogeneity in the context of the users which request Web contents is not taken into account by the servers that deliver them implying that these contents will not always suit their needs. In the particular case of e-learning platforms this issue is especially critical due to the fact that it puts at stake the knowledge acquired by their users. In the following paper we present a system that aims to provide the dotLRN e-learning platform with the capability to adapt to its users context. By integrating dotLRN with a multi-agent hypermedia system, online courses being undertaken by students as well as their learning environment are adapted in real time