Baysian Model Averaging, Learning and Model Selection

Agents have two forecasting models, one consistent with the unique rational expectations equilibrium, another that assumes a time-varying parameter structure. When agents use Bayesian updating to choose between models in a self-referential system, we find that learning dynamics lead to selection of one of the two models. However, there are parameter regions for which the non-rational forecasting model is selected in the long-run. A key structural parameter governing outcomes measures the degree of expectations feedback in Muth's model of price determination.

New roles for community pharmacists in modern health care systems: a challenge for pharmacy education and research.

The academic activities led by the Unit of Community Pharmacy can be classified as translational. Our group is interested in person-centered pharmaceutical services aimed at a more responsible use of drugs (effectiveness, safety, efficiency) in collaboration with physicians and other health care professionals in a primary care setting. The following domains of education and research are high priorities for our group: medication therapy management, medication adherence, integrated care, individualization of therapies, care management for the elderly and e-health.

A multi-purpose grammar generating a multi-scale integrated analysis of Laos

In this study we propose an application of the MuSIASEM approach which is used to provide an integrated analysis of Laos across different scales. With the term “integrated analysis across scales” we mean the generation of a series of packages of quantitative indicators, characterizing the performance of the socioeconomic activities performed in Laos when considering: (i) different hierarchical levels of organization (farming systems described at the level of household, rural villages, regions of Laos, the whole country level); and (ii) different dimensions of analysis (economic dimension, social dimension, ecological dimension, technical dimension). What is relevant in this application is that the information carried out by these different packages of indicators is integrated in a system of accounting which establishes interlinkages across these indicators. This is a essential feature to study sustainability trade-offs and to build more robust scenarios of possible changes. The multi-scale integrated representation presented in this study is based on secondary data (gathered in a three year EU project – SEAtrans and integrated by other available statistical sources) and it is integrated in GIS, when dealing with the spatial representation of Laos. However, even if we use data referring to Laos, the goal of this study is not that of providing useful information about a practical policy issue of Laos, but rather, to illustrate the possibility of using a multipurpose grammar to produce an integrated set of sustainability indicators at three different levels: (i) local; (ii) meso; (iii) macro level. The technical issue addressed is the simultaneous adoption of two multi-level matrices – one referring to a characterization of human activity over a set of different categories, and another referring to a characterization of land uses over the same set of categories. In this way, it becomes possible to explain the characteristics of Laos (an integrated set of indicators defining the performance of the whole country) in relation to the characteristics of the rural Laos and urban Laos. The characteristics of rural Laos, can be explained using the characteristics of three regions defined within Laos (Northern Laos, Central Laos and Southern Laos), which in turn can be defined (using an analogous package of indicators), starting from the characteristics of three main typologies of farming systems found in the regions.

Complementary function and integrated wiring of the evolutionarily distinct Drosophila olfactory subsystems.

To sense myriad environmental odors, animals have evolved multiple, large families of divergent olfactory receptors. How and why distinct receptor repertoires and their associated circuits are functionally and anatomically integrated is essentially unknown. We have addressed these questions through comprehensive comparative analysis of the Drosophila olfactory subsystems that express the ionotropic receptors (IRs) and odorant receptors (ORs). We identify ligands for most IR neuron classes, revealing their specificity for select amines and acids, which complements the broader tuning of ORs for esters and alcohols. IR and OR sensory neurons exhibit glomerular convergence in segregated, although interconnected, zones of the primary olfactory center, but these circuits are extensively interdigitated in higher brain regions. Consistently, behavioral responses to odors arise from an interplay between IR- and OR-dependent pathways. We integrate knowledge on the different phylogenetic and developmental properties of these receptors and circuits to propose models for the functional contributions and evolution of these distinct olfactory subsystems.

Advanced mapping of environmental data: Geostatistics, Machine Learning and Bayesian Maximum Entropy

This book combines geostatistics and global mapping systems to present an up-to-the-minute study of environmental data. Featuring numerous case studies, the reference covers model dependent (geostatistics) and data driven (machine learning algorithms) analysis techniques such as risk mapping, conditional stochastic simulations, descriptions of spatial uncertainty and variability, artificial neural networks (ANN) for spatial data, Bayesian maximum entropy (BME), and more.

TcruziDB, an Integrated Database, and the WWW Information Server for the Trypanosoma cruzi Genome Project

Data analysis, presentation and distribution is of utmost importance to a genome project. A public domain software, ACeDB, has been chosen as the common basis for parasite genome databases, and a first release of TcruziDB, the Trypanosoma cruzi genome database, is available by ftp from ftp://iris.dbbm.fiocruz.br/pub/genomedb/TcruziDB as well as versions of the software for different operating systems (ftp://iris.dbbm.fiocruz.br/pub/unixsoft/). Moreover, data originated from the project are available from the WWW server at http://www.dbbm.fiocruz.br. It contains biological and parasitological data on CL Brener, its karyotype, all available T. cruzi sequences from Genbank, data on the EST-sequencing project and on available libraries, a T. cruzi codon table and a listing of activities and participating groups in the genome project, as well as meeting reports. T. cruzi discussion lists (tcruzi-l@iris.dbbm.fiocruz.br and tcgenics@iris.dbbm.fiocruz.br) are being maintained for communication and to promote collaboration in the genome project

Importance of influx and efflux systems and xenobiotic metabolizing enzymes in intratumoral disposition of anticancer agents.

In this review, intratumoral drug disposition will be integrated into the wide range of resistance mechanisms to anticancer agents with particular emphasis on targeted protein kinase inhibitors. Six rules will be established: 1. There is a high variability of extracellular/intracellular drug level ratios; 2. There are three main systems involved in intratumoral drug disposition that are composed of SLC, ABC and XME enzymes; 3. There is a synergistic interplay between these three systems; 4. In cancer subclones, there is a strong genomic instability that leads to a highly variable expression of SLC, ABC or XME enzymes; 5. Tumor-expressed metabolizing enzymes play a role in tumor-specific ADME and cell survival and 6. These three systems are involved in the appearance of resistance (transient event) or in the resistance itself. In addition, this article will investigate whether the overexpression of some ABC and XME systems in cancer cells is just a random consequence of DNA/chromosomal instability, hypo- or hypermethylation and microRNA deregulation, or a more organized modification induced by transposable elements. Experiments will also have to establish if these tumor-expressed enzymes participate in cell metabolism or in tumor-specific ADME or if they are only markers of clonal evolution and genomic deregulation. Eventually, the review will underline that the fate of anticancer agents in cancer cells should be more thoroughly investigated from drug discovery to clinical studies. Indeed, inhibition of tumor expressed metabolizing enzymes could strongly increase drug disposition, specifically in the target cells resulting in more efficient therapies.

Information systems for water resources management improvement in developing countries

Water resources management, as also water service provision projects in developing countries have difficulties to take adequate decisions due to scarce reliable information, and a lack of proper information managing. Some appropriate tools need to be developed in order to improve decision making to improve water management and access of the poorest, through the design of Decision Support Systems (DSS). On the one side, a DSS for developing co-operation projects on water access improvement has been developed. Such a tool has specific context constrains (structure of the system, software requirements) and needs (Logical Framework Approach monitoring, organizational-learning, accountability and evaluation) that shall be considered for its design. Key aspects for its successful implementation have appeared to be a participatory design of the system and support of the managerial positions at the inception phase. A case study in Tanzania was conducted, together with the Spanish NGO ONGAWA – Ingeniería para el Desarrollo. On the other side, DSS are required also to improve decision making on water management resources in order to achieve a sustainable development that not only improves the living conditions of the population in developing countries, but that also does not hinder opportunities of the poorest on those context. A DSS made to fulfil these requirements shall be using information from water resources modelling, as also on the environment and the social context. Through the research, a case study has been conducted in the Central Rift Valley of Ethiopia, an endhorreic basin 160 km south of Addis Ababa. There, water has been modelled using ArcSWAT, a physically based model which can assess the impact of land management practices on large complex watersheds with varying soils, land use and management conditions over long periods of time. Moreover, governance on water and environment as also the socioeconomic context have been studied.

An Integrated Work Force Planning Strategy For The Health Services 2009 - 2012

Workforce planning identifies the composition of the workforce required to deliver health service goals. It encompasses a range of human resource activities aimed at the short, medium and long-term. Workforce planning that is integrated with service and financial planning offers the best opportunity for linking human resource decisions to the strategic goals for the health services. Systems and structures are required to support and develop workforce planning activities

OER as a Model for Enhanced Teaching and Learning

This article presents preliminary findings from a research study conducted by the Institute for the Study of Knowledge Management in Education on the role of open educational resources (OER) in transforming pedagogy. Based on a study of art and humanities teachers participating in an OER training network, the study reveals how exposure to OER resources and tools support collaboration among teachers, as well as new conversations about teaching practices. These findings have implications for engaging teachers in adopting new OER use practices, and for how OER can be integrated as a model for innovation in teaching and in resource development.

Open Learning Network : the evidence of OER impact

Much of the initial work on Open Educational Resources (OER) has inevitably concentrated on how to produce the resources themselves and to establish the idea in the community. It is now eight years since the term OER was first used and more than ten years since the concept of open content was described and a greater focus is now emerging on the way in which OER can influence policy and change the way in which educational systems help people learn. The Open University UK and Carnegie Mellon University are working in partnership on the OLnet (Open Learning Network), funded by The William and Flora Hewlett Foundation with the aims to search out the evidence for use and reuse of OER and to establish a network for information sharing about research in the field. This means both gathering evidence and developing approaches for how to research and understand ways to learn in a more open world, particularly linked to OER, but also looking at other influences.

A Classification of Tools for Learning Logic

A table showing a comparison and classification of tools (intelligent tutoring systems) for e-learning of Logic at a college level.

Unpacking the cognitive map: the parallel map theory of hippocampal function

In the parallel map theory, the hippocampus encodes space with 2 mapping systems. The bearing map is constructed primarily in the dentate gyrus from directional cues such as stimulus gradients. The sketch map is constructed within the hippocampus proper from positional cues. The integrated map emerges when data from the bearing and sketch maps are combined. Because the component maps work in parallel, the impairment of one can reveal residual learning by the other. Such parallel function may explain paradoxes of spatial learning, such as learning after partial hippocampal lesions, taxonomic and sex differences in spatial learning, and the function of hippocampal neurogenesis. By integrating evidence from physiology to phylogeny, the parallel map theory offers a unified explanation for hippocampal function.

Semi-online neural-Q_leaming for real-time robot learning

Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior

Autonomous underwater vehicle control using reinforcement learning policy search methods

Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task