Modelling shared attention through relational reinforcement learning

Shared attention is a type of communication very important among human beings. It is sometimes reserved for the more complex form of communication being constituted by a sequence of four steps: mutual gaze, gaze following, imperative pointing and declarative pointing. Some approaches have been proposed in Human-Robot Interaction area to solve part of shared attention process, that is, the most of works proposed try to solve the first two steps. Models based on temporal difference, neural networks, probabilistic and reinforcement learning are methods used in several works. In this article, we are presenting a robotic architecture that provides a robot or agent, the capacity of learning mutual gaze, gaze following and declarative pointing using a robotic head interacting with a caregiver. Three learning methods have been incorporated to this architecture and a comparison of their performance has been done to find the most adequate to be used in real experiment. The learning capabilities of this architecture have been analyzed by observing the robot interacting with the human in a controlled environment. The experimental results show that the robotic head is able to produce appropriate behavior and to learn from sociable interaction.

Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning to Optimization of Broad-Band Reflector Antennas Satellite

This paper aims to provide an improved NSGA-II (Non-Dominated Sorting Genetic Algorithm-version II) which incorporates a parameter-free self-tuning approach by reinforcement learning technique, called Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning (NSGA-RL). The proposed method is particularly compared with the classical NSGA-II when applied to a satellite coverage problem. Furthermore, not only the optimization results are compared with results obtained by other multiobjective optimization methods, but also guarantee the advantage of no time-spending and complex parameter tuning.

Evaluation of Vickers hardness of different types of acrylic denture base resins with and without glass fibre reinforcement

Objective: To evaluate the Vickers hardness of different acrylic resins for denture bases with and without the addition of glass fibres. Background: It has been suggested that different polymerisation methods, as well as the addition of glass fibre (FV) might improve the hardness of acrylic. Materials and methods: Five types of acrylic resin were tested: Vipi Wave (VW), microwave polymerisation; Vipi Flash (VF), auto-polymerisation; Lucitone (LT), QC20 (QC) and Vipi Cril (VC), conventional heat-polymerisation, all with or without glass fibre reinforcement (GFR) and distributed into 10 groups (n = 12). Specimens were then submitted to Vickers hardness testing with a 25-g load for 30 s. All data were submitted to ANOVA and Tukey's HSD test. Results: A significant statistical difference was observed with regard to the polymerisation method and the GFR (p < 0.05). Without the GFR, the acrylic resin VC presented the highest hardness values, and VF and LT presented the lowest. In the presence of GFR, VC resin still presented the highest Vickers hardness values, and VF and QC presented the lowest. Conclusions: The acrylic resin VC and VW presented higher hardness values than VF and QC resins. Moreover, GFR increased the Vickers hardness of resins VW, VC and LT.

STATE INSTITUTIONS, POWER, AND SOCIAL NETWORKS IN BRAZILIAN URBAN POLICIES

A large historiographic tradition has studied the Brazilian state, yet we know relatively little about its internal dynamics and particularities. The role of informal, personal, and unintentional ties has remained underexplored in most policy network studies, mainly because of the pluralist origin of that tradition. It is possible to use network analysis to expand this knowledge by developing mesolevel analysis of those processes. This article proposes an analytical framework for studying networks inside policy communities. This framework considers the stable and resilient patterns that characterize state institutions, especially in contexts of low institutionalization, particularly those found in Latin America and Brazil. The article builds on research on urban policies in Brazil to suggest that networks made of institutional and personal ties structure state organizations internally and insert them,into broader political scenarios. These networks, which I call state fabric, frame politics, influence public policies, and introduce more stability and predictability than the majority of the literature usually considers. They also form a specific power resource-positional power, associated with the positions that political actors occupy-that influences politics inside and around the state.

Characterization of suramin binding sites on the human group IIA secreted phospholipase A(2) by site-directed mutagenesis and molecular dynamics simulation

Suramin is a polysulphonated naphthylurea with inhibitory activity against the human secreted group IIA phospholipase A(2) (hsPLA2GIIA), and we have investigated suramin binding to recombinant hsPLA2GIIA using site-directed mutagenesis and molecular dynamics (MD) simulations. The changes in suramin binding affinity of 13 cationic residue mutants of the hsPLA2GIIA was strongly correlated with alterations in the inhibition of membrane damaging activity of the protein. Suramin binding to hsPLA2GIIA was also studied by MD simulations, which demonstrated that altered intermolecular potential energy of the suramin/mutant complexes was a reliable indicator of affinity change. Although residues in the C-terminal region play a major role in the stabilization of the hsPLA2GIIA/suramin complex, attractive and repulsive hydrophobic and electrostatic interactions with residues throughout the protein together with the adoption of a bent suramin conformation, all contribute to the stability of the complex. Analysis of the h5PLA2GIIA/suramin interactions allows the prediction of the properties of suramin analogues with improved binding and higher affinities which may be candidates for novel phospholipase A(2) inhibitors. (C) 2012 Elsevier Inc. All rights reserved.

Frequency and precision of feedback and the adaptive process of learning a dual motor task

This work investigated the effects of frequency and precision of feedback on the learning of a dual-motor task. One hundred and twenty adults were randomly assigned to six groups of different knowledge of results (KR), frequency (100%, 66% or 33%) and precision (specific or general) levels. In the stabilization phase, participants performed the dual task (combination of linear positioning and manual force control) with the provision of KR. Ten non-KR adaptation trials were performed for the same task, but with the introduction of an electromagnetic opposite traction force. The analysis showed a significant main effect for frequency of KR. The participants who received KR in 66% of the stabilization trials showed superior adaptation performance than those who received 100% or 33%. This finding reinforces that there is an optimal level of information, neither too high nor too low, for motor learning to be effective.

Design of laminated piezocomposite shell transducers with arbitrary fiber orientation using topology optimization approach

Sensor and actuator based on laminated piezocomposite shells have shown increasing demand in the field of smart structures. The distribution of piezoelectric material within material layers affects the performance of these structures; therefore, its amount, shape, size, placement, and polarization should be simultaneously considered in an optimization problem. In addition, previous works suggest the concept of laminated piezocomposite structure that includes fiber-reinforced composite layer can increase the performance of these piezoelectric transducers; however, the design optimization of these devices has not been fully explored yet. Thus, this work aims the development of a methodology using topology optimization techniques for static design of laminated piezocomposite shell structures by considering the optimization of piezoelectric material and polarization distributions together with the optimization of the fiber angle of the composite orthotropic layers, which is free to assume different values along the same composite layer. The finite element model is based on the laminated piezoelectric shell theory, using the degenerate three-dimensional solid approach and first-order shell theory kinematics that accounts for the transverse shear deformation and rotary inertia effects. The topology optimization formulation is implemented by combining the piezoelectric material with penalization and polarization model and the discrete material optimization, where the design variables describe the amount of piezoelectric material and polarization sign at each finite element, with the fiber angles, respectively. Three different objective functions are formulated for the design of actuators, sensors, and energy harvesters. Results of laminated piezocomposite shell transducers are presented to illustrate the method. Copyright (C) 2012 John Wiley & Sons, Ltd.