DAT1 polymorphism determines L-DOPA effects on learning about others' prosociality.

Despite that a wealth of evidence links striatal dopamine to individualś reward learning performance in non-social environments, the neurochemical underpinnings of such learning during social interaction are unknown. Here, we show that the administration of 300 mg of the dopamine precursor L-DOPA to 200 healthy male subjects influences learning about a partners' prosocial preferences in a novel social interaction task, which is akin to a repeated trust game. We found learning to be modulated by a well-established genetic marker of striatal dopamine levels, the 40-bp variable number tandem repeats polymorphism of the dopamine transporter (DAT1 polymorphism). In particular, we found that L-DOPA improves learning in 10/10R genoype subjects, who are assumed to have lower endogenous striatal dopamine levels and impairs learning in 9/10R genotype subjects, who are assumed to have higher endogenous dopamine levels. These findings provide first evidence for a critical role of dopamine in learning whether an interaction partner has a prosocial or a selfish personality. The applied pharmacogenetic approach may open doors to new ways of studying psychiatric disorders such as psychosis, which is characterized by distorted perceptions of others' prosocial attitudes.

Simulation of SLA-based VM-scaling algorithms for cloud-distributed applications

Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.

Object-Based Customization of Learning Content: Potentials and Pitfalls

Specification consortia and standardization bodies concentrate on e-Learning objects to en-sure reusability of content. Learning objects may be collected in a library and used for deriv-ing course offerings that are customized to the needs of different learning communities. How-ever, customization of courses is possible only if the logical dependencies between the learn-ing objects are known. Metadata for describing object relationships have been proposed in several e-Learning specifications. This paper discusses the customization potential of e-Learning objects but also the pitfalls that exist if content is customized inappropriately.

THE MEASUREMENT OF HUMANISTIC AND DEHUMANISTIC BEHAVIORS IN HOSPITAL NURSING ENVIRONMENTS

The purpose of this investigation was to develop a reliable scale to measure the social environment of hospital nursing units according to the degree of humanistic and dehumanistic behaviors as perceived by nursing staff in hospitals. The study was based on a conceptual model proposed by Jan Howard, a sociologist. After reviewing the literature relevant to personalization of care, analyzing interviews with patients in various settings, and studying biological, psychological, and sociological frames of reference, Howard proposed the following necessary conditions for humanized health care. They were the dimensions of Irreplaceability, Holistic Selves, Freedom of Action, Status Equality, Shared Decision Making and Responsibility, Empathy, and Positive Affect.^ It was proposed that a scale composed of behaviors which reflected Howard's dimensions be developed within the framework of the social environment of nursing care units in hospitals. Nursing units were chosen because hospitals are traditionally organized around nursing care units and because patients spend the majority of their time in hospitals interacting with various levels of nursing personnel.^ Approximately 180 behaviors describing both patient and nursing staff behaviors which occur on nursing units were developed. Behaviors which were believed to be humanistic as well as dehumanistic were included. The items were classified under the dimensions of Howard's model by a purposively selected sample of 42 nurses representing a broad range of education, experience, and clinical areas. Those items with a high degree of agreement, at least 50%, were placed in the questionnaire. The questionnaire consisted of 169 items including six items from the Marlowe Crowne Social Desirability Scale (Short Form).^ The questionnaire, the Social Environment Scale, was distributed to the entire 7 to 3 shift nursing staff (603) of four hospitals including a public county specialty hospital, a public county general and acute hospital, a large university affiliated hospital with all services, and a small general community hospital. Staff were asked to report on a Likert type scale how often the listed behaviors occurred on their units. Three hundred and sixteen respondents (52% of the population) participated in the study.^ An item analysis was done in which each item was examined in relationship to its correlation to its own dimension total and to the totals of the other dimensions. As a result of this analysis, three dimensions, Positive Affect, Irreplaceability, and Freedom of Action were deleted from the scale. The final scale consisted of 70 items with 26 in Shared Decision Making and Responsibility, 25 in Holistic Selves, 12 in Status Equality, and seven in Empathy. The alpha coefficient was over .800 for all scales except Empathy which was .597.^ An analysis of variance by hospital was performed on the means of each dimension of the scale. There was a statistically significant difference between hospitals with a trend for the public hospitals to score lower on the scale than the university or community hospitals. That the scale scores should be lower in crowded, understaffed public hospitals was not unexpected and reflected that the scale had some discriminating ability. These differences were still observed after adjusting for the effect of Social Desirability.^ In summary, there is preliminary evidence based on this exploratory investigation that a reliable scale based on at least four dimensions from Howard's model could be developed to measure the concept of humanistic health care in hospital settings. ^

The Comprehensive Assessment of Leadership for Learning: A Next Generation Formative Evaluation and Feedback System

Recent developments in federal policy have prompted the creation of state evaluation frameworks for principals and teachers that hold educators accountable for effective practices and student outcomes. These changes have created a demand for formative evaluation instruments that reflect current accountability pressures and can be used by schools to focus school improvement and leadership development efforts. The Comprehensive Assessment of Leadership for Learning (CALL) is a next generation, 360-degree on-line assessment and feedback system that reflect best practices in feedback design. Some unique characteristics of CALL include a focus on: leadership distributed throughout the school rather than as carried out by an individual leader; assessment of leadership tasks rather than perceptions of leadership practice; a focus on larger complex systems of middle and high school; and transparency of assessment design. This paper describes research contributing to the design and validation of the CALL survey instrument.

Adaptive fuzzy knowledge-based systems for control metabots' mobility on virtual environments

The confluence of three-dimensional (3D) virtual worlds with social networks imposes on software agents, in addition to conversational functions, the same behaviours as those common to human-driven avatars. In this paper, we explore the possibilities of the use of metabots (metaverse robots) with motion capabilities in complex virtual 3D worlds and we put forward a learning model based on the techniques used in evolutionary computation for optimizing the fuzzy controllers which will subsequently be used by metabots for moving around a virtual environment.

Distributed Fault Diagnosis Using Bayesian Reasoning in MAGNETO

Many of the emerging telecom services make use of Outer Edge Networks, in particular Home Area Networks. The configuration and maintenance of such services may not be under full control of the telecom operator which still needs to guarantee the service quality experienced by the consumer. Diagnosing service faults in these scenarios becomes especially difficult since there may be not full visibility between different domains. This paper describes the fault diagnosis solution developed in the MAGNETO project, based on the application of Bayesian Inference to deal with the uncertainty. It also takes advantage of a distributed framework to deploy diagnosis components in the different domains and network elements involved, spanning both the telecom operator and the Outer Edge networks. In addition, MAGNETO features self-learning capabilities to automatically improve diagnosis knowledge over time and a partition mechanism that allows breaking down the overall diagnosis knowledge into smaller subsets. The MAGNETO solution has been prototyped and adapted to a particular outer edge scenario, and has been further validated on a real testbed. Evaluation of the results shows the potential of our approach to deal with fault management of outer edge networks.

New Methodology for Integrating Teams into Multidisciplinary Project Based Learning

This paper describes the collaboration among students and professors in four different subjects, to develop multidisciplinary projects. The objective is to simulate the conditions in a company environment. A new methodology based on student interaction and content development in a Wiki environment has been developed. The collaborative server created an ‘out of the classroom’ discussion forum for students of different subjects, and allowed them to compile a ‘project work’ portfolio. Students and professors participated with enthusiasm, due to the correct well-distributed work and the easiness of use of the selected platform in which only an internet connected computer is needed to create and to discuss the multidisciplinary projects. Quality of developed projects has been dramatically improved due to integration of results provided from the different teams.

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

Diffusion Gradient Temporal Difference for Cooperative Reinforcement Learning with Linear Function Approximation

We introduce a diffusion-based algorithm in which multiple agents cooperate to predict a common and global statevalue function by sharing local estimates and local gradient information among neighbors. Our algorithm is a fully distributed implementation of the gradient temporal difference with linear function approximation, to make it applicable to multiagent settings. Simulations illustrate the benefit of cooperation in learning, as made possible by the proposed algorithm.

Monitoring the communication competence in an innovative context of project management learning

This document presents an innovative, formal educational initiative that is aimed at enhancing the development of engineering students' specific competences. The subject of project management is the common theoretical and practical framework that articulates an experience that is carried out by multidisciplinary groups. Full utilization of Web 2.0 platforms and Project Based Learning constitutes the applied methodology. More specifically, this study focuses on monitoring communication competence when working in virtual environments, providing an ad-hoc rubric as a final result.

Decentralized multi-tasks distribution in heterogeneous robot teams by means of ant colony optimization and learning automata

This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-election of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested on decentralized solution where the robots themselves autonomously and in an individual manner, are responsible of selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-tasks distribution problem and we propose a solution using two different approaches by applying Ant Colony Optimization-based deterministic algorithms as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithm, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

Response threshold models and stochastic learning automata for self-coordination of heterogeneous multi-task distribution in multi-robot systems.

This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-selection of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested in a decentralized solution where the robots themselves autonomously and in an individual manner, are responsible for selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-task distribution problem and we propose a solution using two different approaches by applying Response Threshold Models as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

Contribution to flexible service coordination in mobile prosumer environments

Este trabajo de Tesis se desarrolla en el marco de los escenarios de ejecución distribuida de servicios móviles y contribuye a la definición y desarrollo del concepto de usuario prosumer. El usuario prosumer se caracteriza por utilizar su teléfono móvil para crear, proveer y ejecutar servicios. Este nuevo modelo de usuario contribuye al avance de la sociedad de la información, ya que el usuario prosumer se transforma de creador de contenidos a creador de servicios (estos últimos formados por contenidos y la lógica para acceder a ellos, procesarlos y representarlos). El objetivo general de este trabajo de Tesis es la provisión de un modelo de creación, distribución y ejecución de servicios para entorno móvil que permita a los usuarios no programadores (usuarios prosumer), pero expertos en un determinado dominio, crear y ejecutar sus propias aplicaciones y servicios. Para ello se definen, desarrollan e implementan metodologías, procesos, algoritmos y mecanismos adaptables a dominios específicos, para construir entornos de ejecución distribuida de servicios móviles para usuarios prosumer. La provisión de herramientas de creación adaptadas a usuarios no expertos es una tendencia actual que está siendo desarrollada en distintos trabajos de investigación. Sin embargo, no se ha propuesto una metodología de desarrollo de servicios que involucre al usuario prosumer en el proceso de diseño, desarrollo, implementación y validación de servicios. Este trabajo de Tesis realiza un estudio de las metodologías y tecnologías más innovadoras relacionadas con la co‐creación y utiliza este análisis para definir y validar una metodología que habilita al usuario para ser el responsable de la creación de servicios finales. Siendo los entornos móviles prosumer (mobile prosumer environments) una particularización de los entornos de ejecución distribuida de servicios móviles, en este trabajo se tesis se investiga en técnicas de adaptación, distribución, coordinación de servicios y acceso a recursos identificando como requisitos las problemáticas de este tipo de entornos y las características de los usuarios que participan en los mismos. Se contribuye a la adaptación de servicios definiendo un modelo de variabilidad que soporte la interdependencia entre las decisiones de personalización de los usuarios, incorporando mecanismos de guiado y detección de errores. La distribución de servicios se implementa utilizando técnicas de descomposición en árbol SPQR, cuantificando el impacto de separar cualquier servicio en distintos dominios. Considerando el plano de comunicaciones para la coordinación en la ejecución de servicios distribuidos hemos identificado varias problemáticas, como las pérdidas de enlace, conexiones, desconexiones y descubrimiento de participantes, que resolvemos utilizando técnicas de diseminación basadas en publicación subscripción y algoritmos Gossip. Para lograr una ejecución flexible de servicios distribuidos en entorno móvil, soportamos la adaptación a cambios en la disponibilidad de los recursos, proporcionando una infraestructura de comunicaciones para el acceso uniforme y eficiente a recursos. Se han realizado validaciones experimentales para evaluar la viabilidad de las soluciones propuestas, definiendo escenarios de aplicación relevantes (el nuevo universo inteligente, prosumerización de servicios en entornos hospitalarios y emergencias en la web de la cosas). Abstract This Thesis work is developed in the framework of distributed execution of mobile services and contributes to the definition and development of the concept of prosumer user. The prosumer user is characterized by using his mobile phone to create, provide and execute services. This new user model contributes to the advancement of the information society, as the prosumer is transformed from producer of content, to producer of services (consisting of content and logic to access them, process them and represent them). The overall goal of this Thesis work is to provide a model for creation, distribution and execution of services for the mobile environment that enables non‐programmers (prosumer users), but experts in a given domain, to create and execute their own applications and services. For this purpose I define, develop and implement methodologies, processes, algorithms and mechanisms, adapted to specific domains, to build distributed environments for the execution of mobile services for prosumer users. The provision of creation tools adapted to non‐expert users is a current trend that is being developed in different research works. However, it has not been proposed a service development methodology involving the prosumer user in the process of design, development, implementation and validation of services. This thesis work studies innovative methodologies and technologies related to the co‐creation and relies on this analysis to define and validate a methodological approach that enables the user to be responsible for creating final services. Being mobile prosumer environments a specific case of environments for distributed execution of mobile services, this Thesis work researches in service adaptation, distribution, coordination and resource access techniques, and identifies as requirements the challenges of such environments and characteristics of the participating users. I contribute to service adaptation by defining a variability model that supports the dependency of user personalization decisions, incorporating guiding and error detection mechanisms. Service distribution is implemented by using decomposition techniques based on SPQR trees, quantifying the impact of separating any service in different domains. Considering the communication level for the coordination of distributed service executions I have identified several problems, such as link losses, connections, disconnections and discovery of participants, which I solve using dissemination techniques based on publish‐subscribe communication models and Gossip algorithms. To achieve a flexible distributed service execution in mobile environments, I support adaptation to changes in the availability of resources, while providing a communication infrastructure for the uniform and efficient access to resources. Experimental validations have been conducted to assess the feasibility of the proposed solutions, defining relevant application scenarios (the new intelligent universe, service prosumerization in hospitals and emergency situations in the web of things).