Hierarchical modelling of timber reference properties using probabilistic methods: Maximum Likelihood Method, Bayesian Methods and Probability Networks

In recent decades, an increased interest has been evidenced in the research on multi-scale hierarchical modelling in the field of mechanics, and also in the field of wood products and timber engineering. One of the main motivations for hierar-chical modelling is to understand how properties, composition and structure at lower scale levels may influence and be used to predict the material properties on a macroscopic and structural engineering scale. This chapter presents the applicability of statistic and probabilistic methods, such as the Maximum Likelihood method and Bayesian methods, in the representation of timber’s mechanical properties and its inference accounting to prior information obtained in different importance scales. These methods allow to analyse distinct timber’s reference properties, such as density, bending stiffness and strength, and hierarchically consider information obtained through different non, semi or destructive tests. The basis and fundaments of the methods are described and also recommendations and limitations are discussed. The methods may be used in several contexts, however require an expert’s knowledge to assess the correct statistic fitting and define the correlation arrangement between properties.

Asociatividad y redes interorganizacionales. El caso de la Red Social de la 5ta. Associativity and interorganizational networks. The case of the Social Network of "la 5ta".

En investigaciones anteriores el equipo trabajó sobre el concepto de asociatividad en las prácticas de emprendimientos socioeconómicos y cooperativas surgidos luego de la crisis del 2001 en Argentina. Las conclusiones de dichas investigaciones se agrupan en dos categorías. La primera identifica como un obstáculo importante para generar y sostener la asociatividad, al elevado grado de desconfianza y fragmentación del tejido social, que dificulta la conformación de formas organizacionales asociativas más allá de las emprendidas por personas vinculadas por lazos afectivos previos. La segunda categoría de conclusiones corresponde a las dificultadas asociadas a los niveles de formalidad requeridos por las políticas públicas que promueven la constitución de formas asociativas.Sobre estos antecedentes se propone el análisis otras formas asociativas de mayor envergadura tales como las redes interorganizacionales, que superan la asociatividad entre individuos e incluyen a diversas organizaciones (de la sociedad civil, actores estatales, instituciones educativas, cooperativas, etc.). Estas redes, que incluyen a las formas asociativas estudiadas anteriormente por el equipo, se diferencian de ellas en que los vínculos trascienden el contexto primario de los actores, no necesariamente se asientan sobre estructuras de coordinación formales y cuentan con una cierta trayectoria de construcción colectiva que sirve de base y sustento a proyectos sociales en sectores de alta vulnerabilidad. El objetivo de la investigación es describir y analizar las características de la asociatividad en una de estas redes existente en la ciudad de Córdoba, en especial en lo que hace al diseño organizacional y funcionamiento asociativo, identificando el proceso de incidencia de la misma en políticas públicas y los factores que favorecen y obstaculizan ese proceso. La metodología consiste en la construcción conjunta, con los propios actores, de los problemas de investigación para desde allí comprender y sistematizar sus propias prácticas con el objetivo de generar un conocimiento capaz de potenciar su dinámica y enriquecer la construcción teórica en torno a estas formas organizacionales. La red elegida es la Red Social de la 5ta, compuesta por alrededor de 30 organizaciones entre las que se cuentan OSC y organismos públicos de distintos niveles (provincial y municipal). Funciona desde el año 1998 en la zona sudeste de la ciudad de Córdoba uno de los sectores que concentra los índices más altos de pobreza y morbilidad y mortalidad materno infantil de la ciudad. El deterioro de la situación económica y el progresivo abandono del Estado han convertido gran parte de la zona donde se articula la Red en una zona marginal, adjudicataria en el imaginario público del estigma de peligrosidad. En este marco, el objetivo de la Red es mejorar a calidad de vida de la comunidad a través de acciones conjuntas y del establecimiento de acuerdos con otros actores institucionales.

Development of a data acquisition system to characterise sustainable energy technologies and to support Web-Based learning (DAQ-WBL)

Driven by concerns about rising energy costs, security of supply and climate change a new wave of Sustainable Energy Technologies (SET’s) have been embraced by the Irish consumer. Such systems as solar collectors, heat pumps and biomass boilers have become common due to government backed financial incentives and revisions of the building regulations. However, there is a deficit of knowledge and understanding of how these technologies operate and perform under Ireland’s maritime climate. This AQ-WBL project was designed to address both these needs by developing a Data Acquisition (DAQ) system to monitor the performance of such technologies and a web-based learning environment to disseminate performance characteristics and supplementary information about these systems. A DAQ system consisting of 108 sensors was developed as part of Galway-Mayo Institute of Technology’s (GMIT’s) Centre for the Integration of Sustainable EnergyTechnologies (CiSET) in an effort to benchmark the performance of solar thermal collectors and Ground Source Heat Pumps (GSHP’s) under Irish maritime climate, research new methods of integrating these systems within the built environment and raise awareness of SET’s. It has operated reliably for over 2 years and has acquired over 25 million data points. Raising awareness of these SET’s is carried out through the dissemination of the performance data through an online learning environment. A learning environment was created to provide different user groups with a basic understanding of a SET’s with the support of performance data, through a novel 5 step learning process and two examples were developed for the solar thermal collectors and the weather station which can be viewed at http://www.kdp 1 .aquaculture.ie/index.aspx. This online learning environment has been demonstrated to and well received by different groups of GMIT’s undergraduate students and plans have been made to develop it further to support education, awareness, research and regional development.

On the role of temporal context in human reinforcement learning

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2011

Auditory gating in the ventral striatum and auditory cortex : the role of stimulus-locking and the influence of discrimination learning

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2014

Ab initio modeling and molecular dynamics simulation of the alpha 1b-adrenergic receptor activation.

This work describes the ab initio procedure employed to build an activation model for the alpha 1b-adrenergic receptor (alpha 1b-AR). The first version of the model was progressively modified and complicated by means of a many-step iterative procedure characterized by the employment of experimental validations of the model in each upgrading step. A combined simulated (molecular dynamics) and experimental mutagenesis approach was used to determine the structural and dynamic features characterizing the inactive and active states of alpha 1b-AR. The latest version of the model has been successfully challenged with respect to its ability to interpret and predict the functional properties of a large number of mutants. The iterative approach employed to describe alpha 1b-AR activation in terms of molecular structure and dynamics allows further complications of the model to allow prediction and interpretation of an ever-increasing number of experimental data.

Towards and inclusive definition of e-learning

L'estudi té com a objectiu la construcció d'una definició actual i integradora del concepte d'e-learning, que sigui acceptada per la major part de la comunitat científica i que serveixi com a referent pels estudiosos i professionals d'aquesta temàtica.

Towards Direct Policy Search Reinforcement Learning for Robot Control

This paper proposes a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, when using RL, has been to apply value function based algorithms, the system here detailed is characterized by the use of direct policy search methods. Rather than approximating a value function, these methodologies approximate a policy using an independent function approximator with its own parameters, trying to maximize the future expected reward. The policy based algorithm presented in this paper is used for learning the internal state/action mapping of a behavior. In this preliminary work, we demonstrate its feasibility with simulated experiments using the underwater robot GARBI in a target reaching task

Robust control of structures subject to uncertain disturbances and actuator dynamics

The objective the present research is try to find some control design strategies, which must be effective and closed to the real operation conditions. As a novel contribution to structural control strategies, the theories of Interval Modal Arithmetic, Backstepping Control and QFT (Qualitative Feedback Theory) will be studied. The steps to follow are to develop first new controllers based on the above theories and then to implement the proposed control strategies to different kind of structures. The report is organized as follows. The Chapter 2 presents the state-of-the-art on structural control systems. The chapter 3 presents the most important open problems found in field of structural control. The exploratory work made by the author, research proposal and working plan are given in the Chapter 4

Biana: a software framework for compiling biological interactions and analyzing networks

Background: The analysis and usage of biological data is hindered by the spread of information across multiple repositories and the difficulties posed by different nomenclature systems and storage formats. In particular, there is an important need for data unification in the study and use of protein-protein interactions. Without good integration strategies, it is difficult to analyze the whole set of available data and its properties.Results: We introduce BIANA (Biologic Interactions and Network Analysis), a tool for biological information integration and network management. BIANA is a Python framework designed to achieve two major goals: i) the integration of multiple sources of biological information, including biological entities and their relationships, and ii) the management of biological information as a network where entities are nodes and relationships are edges. Moreover, BIANA uses properties of proteins and genes to infer latent biomolecular relationships by transferring edges to entities sharing similar properties. BIANA is also provided as a plugin for Cytoscape, which allows users to visualize and interactively manage the data. A web interface to BIANA providing basic functionalities is also available. The software can be downloaded under GNU GPL license from http://sbi.imim.es/web/BIANA.php.Conclusions: BIANA's approach to data unification solves many of the nomenclature issues common to systems dealing with biological data. BIANA can easily be extended to handle new specific data repositories and new specific data types. The unification protocol allows BIANA to be a flexible tool suitable for different user requirements: non-expert users can use a suggested unification protocol while expert users can define their own specific unification rules.

Emergence of Cooperation on Static and Dynamic Networks

Game theory is a branch of applied mathematics used to analyze situation where two or more agents are interacting. Originally it was developed as a model for conflicts and collaborations between rational and intelligent individuals. Now it finds applications in social sciences, eco- nomics, biology (particularly evolutionary biology and ecology), engineering, political science, international relations, computer science, and philosophy. Networks are an abstract representation of interactions, dependencies or relationships. Net- works are extensively used in all the fields mentioned above and in many more. Many useful informations about a system can be discovered by analyzing the current state of a network representation of such system. In this work we will apply some of the methods of game theory to populations of agents that are interconnected. A population is in fact represented by a network of players where one can only interact with another if there is a connection between them. In the first part of this work we will show that the structure of the underlying network has a strong influence on the strategies that the players will decide to adopt to maximize their utility. We will then introduce a supplementary degree of freedom by allowing the structure of the population to be modified along the simulations. This modification allows the players to modify the structure of their environment to optimize the utility that they can obtain.

Modeling premartensitic effects in Ni2MnGa: A mean-field and Monte Carlo simulation study

ic first-order transition line ending in a critical point. This critical point is responsible for the existence of large premartensitic fluctuations which manifest as broad peaks in the specific heat, not always associated with a true phase transition. The main conclusion is that premartensitic effects result from the interplay between the softness of the anomalous phonon driving the modulation and the magnetoelastic coupling. In particular, the premartensitic transition occurs when such coupling is strong enough to freeze the involved mode phonon. The implication of the results in relation to the available experimental data is discussed.

Modelling non-industrial private forest landowners' strategic decision making by using logistic regression and neural networks: case of predicting the choice of forest taxation basis

Summary