Adaptive filtering methods for identifying cross-frequency couplings in human EEG.

Oscillations have been increasingly recognized as a core property of neural responses that contribute to spontaneous, induced, and evoked activities within and between individual neurons and neural ensembles. They are considered as a prominent mechanism for information processing within and communication between brain areas. More recently, it has been proposed that interactions between periodic components at different frequencies, known as cross-frequency couplings, may support the integration of neuronal oscillations at different temporal and spatial scales. The present study details methods based on an adaptive frequency tracking approach that improve the quantification and statistical analysis of oscillatory components and cross-frequency couplings. This approach allows for time-varying instantaneous frequency, which is particularly important when measuring phase interactions between components. We compared this adaptive approach to traditional band-pass filters in their measurement of phase-amplitude and phase-phase cross-frequency couplings. Evaluations were performed with synthetic signals and EEG data recorded from healthy humans performing an illusory contour discrimination task. First, the synthetic signals in conjunction with Monte Carlo simulations highlighted two desirable features of the proposed algorithm vs. classical filter-bank approaches: resilience to broad-band noise and oscillatory interference. Second, the analyses with real EEG signals revealed statistically more robust effects (i.e. improved sensitivity) when using an adaptive frequency tracking framework, particularly when identifying phase-amplitude couplings. This was further confirmed after generating surrogate signals from the real EEG data. Adaptive frequency tracking appears to improve the measurements of cross-frequency couplings through precise extraction of neuronal oscillations.

Policy Diffusion: An Agent-Based Approach

Methods like Event History Analysis can show the existence of diffusion and part of its nature, but do not study the process itself. Nowadays, thanks to the increasing performance of computers, processes can be studied using computational modeling. This thesis presents an agent-based model of policy diffusion mainly inspired from the model developed by Braun and Gilardi (2006). I first start by developing a theoretical framework of policy diffusion that presents the main internal drivers of policy diffusion - such as the preference for the policy, the effectiveness of the policy, the institutional constraints, and the ideology - and its main mechanisms, namely learning, competition, emulation, and coercion. Therefore diffusion, expressed by these interdependencies, is a complex process that needs to be studied with computational agent-based modeling. In a second step, computational agent-based modeling is defined along with its most significant concepts: complexity and emergence. Using computational agent-based modeling implies the development of an algorithm and its programming. When this latter has been developed, we let the different agents interact. Consequently, a phenomenon of diffusion, derived from learning, emerges, meaning that the choice made by an agent is conditional to that made by its neighbors. As a result, learning follows an inverted S-curve, which leads to partial convergence - global divergence and local convergence - that triggers the emergence of political clusters; i.e. the creation of regions with the same policy. Furthermore, the average effectiveness in this computational world tends to follow a J-shaped curve, meaning that not only time is needed for a policy to deploy its effects, but that it also takes time for a country to find the best-suited policy. To conclude, diffusion is an emergent phenomenon from complex interactions and its outcomes as ensued from my model are in line with the theoretical expectations and the empirical evidence.Les méthodes d'analyse de biographie (event history analysis) permettent de mettre en évidence l'existence de phénomènes de diffusion et de les décrire, mais ne permettent pas d'en étudier le processus. Les simulations informatiques, grâce aux performances croissantes des ordinateurs, rendent possible l'étude des processus en tant que tels. Cette thèse, basée sur le modèle théorique développé par Braun et Gilardi (2006), présente une simulation centrée sur les agents des phénomènes de diffusion des politiques. Le point de départ de ce travail met en lumière, au niveau théorique, les principaux facteurs de changement internes à un pays : la préférence pour une politique donnée, l'efficacité de cette dernière, les contraintes institutionnelles, l'idéologie, et les principaux mécanismes de diffusion que sont l'apprentissage, la compétition, l'émulation et la coercition. La diffusion, définie par l'interdépendance des différents acteurs, est un système complexe dont l'étude est rendue possible par les simulations centrées sur les agents. Au niveau méthodologique, nous présenterons également les principaux concepts sous-jacents aux simulations, notamment la complexité et l'émergence. De plus, l'utilisation de simulations informatiques implique le développement d'un algorithme et sa programmation. Cette dernière réalisée, les agents peuvent interagir, avec comme résultat l'émergence d'un phénomène de diffusion, dérivé de l'apprentissage, où le choix d'un agent dépend en grande partie de ceux faits par ses voisins. De plus, ce phénomène suit une courbe en S caractéristique, poussant à la création de régions politiquement identiques, mais divergentes au niveau globale. Enfin, l'efficacité moyenne, dans ce monde simulé, suit une courbe en J, ce qui signifie qu'il faut du temps, non seulement pour que la politique montre ses effets, mais également pour qu'un pays introduise la politique la plus efficace. En conclusion, la diffusion est un phénomène émergent résultant d'interactions complexes dont les résultats du processus tel que développé dans ce modèle correspondent tant aux attentes théoriques qu'aux résultats pratiques.

Performance of an ICU ventilator and two turbin-based ventilators dedicated to non invasive ventilation (NIV) in simulated high inspiratory effort and rate: a NIV-bench-study.

INTRODUCTION. The role of turbine-based NIV ventilators (TBV) versus ICU ventilators with NIV mode activated (ICUV) to deliver NIV in case of severe respiratory failure remains debated. OBJECTIVES. To compare the response time and pressurization capacity of TBV and ICUV during simulated NIV with normal and increased respiratory demand, in condition of normal and obstructive respiratory mechanics. METHODS. In a two-chamber lung model, a ventilator simulated normal (P0.1 = 2 mbar, respiratory rate RR = 15/min) or increased (P0.1 = 6 mbar, RR = 25/min) respiratory demand. NIV was simulated by connecting the lung model (compliance 100 ml/mbar; resistance 5 or 20 l/mbar) to a dummy head equipped with a naso-buccal mask. Connections allowed intentional leaks (29 ± 5 % of insufflated volume). Ventilators to test: Servo-i (Maquet), V60 and Vision (Philips Respironics) were connected via a standard circuit to the mask. Applied pressure support levels (PSL) were 7 mbar for normal and 14 mbar for increased demand. Airway pressure and flow were measured in the ventilator circuit and in the simulated airway. Ventilator performance was assessed by determining trigger delay (Td, ms), pressure time product at 300 ms (PTP300, mbar s) and inspiratory tidal volume (VT, ml) and compared by three-way ANOVA for the effect of inspiratory effort, resistance and the ventilator. Differences between ventilators for each condition were tested by oneway ANOVA and contrast (JMP 8.0.1, p\0.05). RESULTS. Inspiratory demand and resistance had a significant effect throughout all comparisons. Ventilator data figure in Table 1 (normal demand) and 2 (increased demand): (a) different from Servo-i, (b) different from V60.CONCLUSION. In this NIV bench study, with leaks, trigger delay was shorter for TBV with normal respiratory demand. By contrast, it was shorter for ICUV when respiratory demand was high. ICUV afforded better pressurization (PTP 300) with increased demand and PSL, particularly with increased resistance. TBV provided a higher inspiratory VT (i.e., downstream from the leaks) with normal demand, and a significantly (although minimally) lower VT with increased demand and PSL.

A vision for change: Report of the Expert Group on Mental Health Policy (2006)

This report, the first comprehensive review of mental health policy since 'Planning for the Future' was published in 1984, makes a series of recommendations for the mental health services, including the closure of all psychiatric hospitals and re-investment of the resources into a community-based mental health service.This resource was contributed by The National Documentation Centre on Drug Use.

Portland Row Community Café

Our Vision is that each individual accessing these service’s be provided with a choice of affordable, nutritious meals in a safe, warm and attractive environment.  We achieve this through the following best practice standards: – Quality service – Maintaining a high quality environment – The highest quality food standard (with choice of meals) Cafes are open to the public from 8am serving breakfast until 11.30 and lunch/dinner from 12-4pm. (open Monday – Friday) Telephone: (01) 8555577 Initiative Type Community Cafés Location Dublin 1

Holles Row Community Café

Our Vision is that each individual accessing these service’s be provided with a choice of affordable, nutritious meals in a safe, warm and attractive environment.  We achieve this through the following best practice standards: – Quality service – Maintaining a high quality environment – The highest quality food standard (with choice of meals) Cafes are open to the public from 8am serving breakfast until 11.30 and lunch/dinner from 12-4pm.(open Monday - Saturday) Telephone: (01) 5515916 Initiative Type Community Cafés Location Dublin 2

A behavior-based scheme using reinforcement learning for autonomous underwater vehicles

This paper presents a hybrid behavior-based scheme using reinforcement learning for high-level control of autonomous underwater vehicles (AUVs). Two main features of the presented approach are hybrid behavior coordination and semi on-line neural-Q_learning (SONQL). Hybrid behavior coordination takes advantages of robustness and modularity in the competitive approach as well as efficient trajectories in the cooperative approach. SONQL, a new continuous approach of the Q_learning algorithm with a multilayer neural network is used to learn behavior state/action mapping online. Experimental results show the feasibility of the presented approach for AUVs

Calibration of a Structured Light-Based Stereo Catadioptric Sensor

Catadioptric sensors are combinations of mirrors and lenses made in order to obtain a wide field of view. In this paper we propose a new sensor that has omnidirectional viewing ability and it also provides depth information about the nearby surrounding. The sensor is based on a conventional camera coupled with a laser emitter and two hyperbolic mirrors. Mathematical formulation and precise specifications of the intrinsic and extrinsic parameters of the sensor are discussed. Our approach overcomes limitations of the existing omni-directional sensors and eventually leads to reduced costs of production

An approach to visual servoing based on coded light

Positioning a robot with respect to objects by using data provided by a camera is a well known technique called visual servoing. In order to perform a task, the object must exhibit visual features which can be extracted from different points of view. Then, visual servoing is object-dependent as it depends on the object appearance. Therefore, performing the positioning task is not possible in presence of non-textured objects or objects for which extracting visual features is too complex or too costly. This paper proposes a solution to tackle this limitation inherent to the current visual servoing techniques. Our proposal is based on the coded structured light approach as a reliable and fast way to solve the correspondence problem. In this case, a coded light pattern is projected providing robust visual features independently of the object appearance

Robust decoupled visual servoing based on structured light

This paper focuses on the problem of realizing a plane-to-plane virtual link between a camera attached to the end-effector of a robot and a planar object. In order to do the system independent to the object surface appearance, a structured light emitter is linked to the camera so that 4 laser pointers are projected onto the object. In a previous paper we showed that such a system has good performance and nice characteristics like partial decoupling near the desired state and robustness against misalignment of the emitter and the camera (J. Pages et al., 2004). However, no analytical results concerning the global asymptotic stability of the system were obtained due to the high complexity of the visual features utilized. In this work we present a better set of visual features which improves the properties of the features in (J. Pages et al., 2004) and for which it is possible to prove the global asymptotic stability

Plane-to-plane positioning from image-based visual servoing and structured light

In this paper we face the problem of positioning a camera attached to the end-effector of a robotic manipulator so that it gets parallel to a planar object. Such problem has been treated for a long time in visual servoing. Our approach is based on linking to the camera several laser pointers so that its configuration is aimed to produce a suitable set of visual features. The aim of using structured light is not only for easing the image processing and to allow low-textured objects to be treated, but also for producing a control scheme with nice properties like decoupling, stability, well conditioning and good camera trajectory

Speculative parallelization of multipath radiosity algorithm

In computer graphics, global illumination algorithms take into account not only the light that comes directly from the sources, but also the light interreflections. This kind of algorithms produce very realistic images, but at a high computational cost, especially when dealing with complex environments. Parallel computation has been successfully applied to such algorithms in order to make it possible to compute highly-realistic images in a reasonable time. We introduce here a speculation-based parallel solution for a global illumination algorithm in the context of radiosity, in which we have taken advantage of the hierarchical nature of such an algorithm

Predictive motion control of a mirosot mobile robot

This paper discusses predictive motion control of a MiRoSoT robot. The dynamic model of the robot is deduced by taking into account the whole process - robot, vision, control and transmission systems. Based on the obtained dynamic model, an integrated predictive control algorithm is proposed to position precisely with either stationary or moving obstacle avoidance. This objective is achieved automatically by introducing distant constraints into the open-loop optimization of control inputs. Simulation results demonstrate the feasibility of such control strategy for the deduced dynamic model

Shape complexity based on mutual information

Shape complexity has recently received attention from different fields, such as computer vision and psychology. In this paper, integral geometry and information theory tools are applied to quantify the shape complexity from two different perspectives: from the inside of the object, we evaluate its degree of structure or correlation between its surfaces (inner complexity), and from the outside, we compute its degree of interaction with the circumscribing sphere (outer complexity). Our shape complexity measures are based on the following two facts: uniformly distributed global lines crossing an object define a continuous information channel and the continuous mutual information of this channel is independent of the object discretisation and invariant to translations, rotations, and changes of scale. The measures introduced in this paper can be potentially used as shape descriptors for object recognition, image retrieval, object localisation, tumour analysis, and protein docking, among others

A New Method for ECG Tracking of Persistent Atrial Fibrillation Termination during Stepwise Ablation

Stepwise radiofrequency catheter ablation (step-CA) has become the treatment of choice for the restoration of sinus rhythm (SR) in patients with long-standing persistent atrial fibrillation (pers-AF). Its success rate appears limited as the amount of ablation to achieve long term SR is unknown. Multiple organization indexes (OIs) have been previously developed to track the organization of AF during step-CA, however, with limited success. We report an adaptive method for tracking AF termination (AF-term) based on OIs characterizing the relationship between harmonic components of atrial activity from the surface ECG of AF activity. By computing their relative evolution during the last two steps preceding AF-term, we found that the performance of our OIs was superior to classical indices to track the efficiency of step-CA "en route" to AF-term. Our preliminary results suggest that the gradual synchronization between the fundamental and its first harmonic of AF activity appears as a promising parameter for predicting AF-term during step-CA.