Bayesian Optimisation for Safe Navigation under Localisation Uncertainty

In outdoor environments, mobile robots are required to navigate through terrain with varying characteristics, some of which might significantly affect the integrity of the platform. Ideally, the robot should be able to identify areas that are safe for navigation based on its own percepts about the environment while avoiding damage to itself. Bayesian optimisation (BO) has been successfully applied to the task of learning a model of terrain traversability while guiding the robot through more traversable areas. An issue, however, is that localisation uncertainty can end up guiding the robot to unsafe areas and distort the model being learnt. In this paper, we address this problem and present a novel method that allows BO to consider localisation uncertainty by applying a Gaussian process model for uncertain inputs as a prior. We evaluate the proposed method in simulation and in experiments with a real robot navigating over rough terrain and compare it against standard BO methods.Comment: To appear in the proceedings of the 18th International Symposium on Robotics Research (ISRR 2017

Kondo effect in a carbon nanotube with spin-orbit interaction and valley mixing: A DM-NRG study

We investigate the effects of spin-orbit interaction (SOI) and valley mixing on the transport and dynamical properties of a carbon nanotube (CNT) quantum dot in the Kondo regime. As these perturbations break the pseudo-spin symmetry in the CNT spectrum but preserve time-reversal symmetry, they induce a finite splitting $\Delta$ between formerly degenerate Kramers pairs. Correspondingly, a crossover from the SU(4) to the SU(2)-Kondo effect occurs as the strength of these symmetry breaking parameters is varied. Clear signatures of the crossover are discussed both at the level of the spectral function as well as of the conductance. In particular, we demonstrate numerically and support with scaling arguments, that the Kondo temperature scales inversely with the splitting $\Delta$ in the crossover regime. In presence of a finite magnetic field, time reversal symmetry is also broken. We investigate the effects of both parallel and perpendicular fields (with respect to the tube's axis), and discuss the conditions under which Kondo revivals may be achieved.Comment: 13 pages, 17 figure

The effects of childbirth on the pelvic-floor

Basically, vaginal delivery is associated with the risk of pelvic floor damage. The pelvic floor sequelae of childbirth includes anal incontinence, urinary incontinence and pelvic organ prolapse. Pathophysiology, incidence and risk factors for the development of the respective problems are reviewed. Where possible, recommendations for reducing the risk of pelvic floor damage are given

Methane in the Baltic and North Seas and a reassessment of the marine emissions of methane

During three measurement campaigns on the Baltic and North Seas, atmospheric and dissolved methane was determined with an automated gas chromatographic system. Area-weighted mean saturation values in the sea surface waters were 113 ± 5% and 395 ± 82% (Baltic Sea, February and July 1992) and 126 ± 8% (south central North Sea, September 1992). On the bases of our data and a compilation of literature data the global oceanic emissions of methane were reassessed by introducing a concept of regional gas transfer coefficients. Our estimates computed with two different air-sea exchange models lie in the range of 11-18 Tg CH4 yr-1. Despite the fact that shelf areas and estuaries only represent a small part of the world's ocean they contribute about 75% to the global oceanic emissions. We applied a simple, coupled, three-layer model to numerically simulate the time dependent variation of the oceanic flux to the atmosphere. The model calculations indicate that even with increasing tropospheric methane concentration, the ocean will remain a source of atmospheric methane

Surface critical exponents at a uniaxial Lifshitz point

Using Monte Carlo techniques, the surface critical behaviour of three-dimensional semi-infinite ANNNI models with different surface orientations with respect to the axis of competing interactions is investigated. Special attention is thereby paid to the surface criticality at the bulk uniaxial Lifshitz point encountered in this model. The presented Monte Carlo results show that the mean-field description of semi-infinite ANNNI models is qualitatively correct. Lifshitz point surface critical exponents at the ordinary transition are found to depend on the surface orientation. At the special transition point, however, no clear dependency of the critical exponents on the surface orientation is revealed. The values of the surface critical exponents presented in this study are the first estimates available beyond mean-field theory.Comment: 10 pages, 7 figures include

The MVGC multivariate Granger causality toolbox: a new approach to Granger-causal inference

Background: Wiener-Granger causality (“G-causality”) is a statistical notion of causality applicable to time series data, whereby cause precedes, and helps predict, effect. It is defined in both time and frequency domains, and allows for the conditioning out of common causal influences. Originally developed in the context of econometric theory, it has since achieved broad application in the neurosciences and beyond. Prediction in the G-causality formalism is based on VAR (Vector AutoRegressive) modelling. New Method: The MVGC Matlab c Toolbox approach to G-causal inference is based on multiple equivalent representations of a VAR model by (i) regression parameters, (ii) the autocovariance sequence and (iii) the cross-power spectral density of the underlying process. It features a variety of algorithms for moving between these representations, enabling selection of the most suitable algorithms with regard to computational efficiency and numerical accuracy. Results: In this paper we explain the theoretical basis, computational strategy and application to empirical G-causal inference of the MVGC Toolbox. We also show via numerical simulations the advantages of our Toolbox over previous methods in terms of computational accuracy and statistical inference. Comparison with Existing Method(s): The standard method of computing G-causality involves estimation of parameters for both a full and a nested (reduced) VAR model. The MVGC approach, by contrast, avoids explicit estimation of the reduced model, thus eliminating a source of estimation error and improving statistical power, and in addition facilitates fast and accurate estimation of the computationally awkward case of conditional G-causality in the frequency domain. Conclusions: The MVGC Toolbox implements a flexible, powerful and efficient approach to G-causal inference. Keywords: Granger causality, vector autoregressive modelling, time series analysi

Foodservice in hospital: development of a theoretical model for patient experience and satisfaction using one hospital in the UK National Health Service as a case study

Hospital foodservice does not operate in isolation but requires the cooperation and integration of several disciplines to provide the ultimate patient experience. The objective of this research was to explore the antecedents to patient satisfaction and experience, including the service element. Accordingly, focus groups were conducted with doctors (n = 4), nurses (n = 5), ward hostesses (n = 3) and patients together with their visitors (n = 10), while open-ended interviews were conducted with the foodservice manager, facilities manager, chief dietitian, orthopaedic ward dietitian and chief pharmacist. Themes centred on ‘patients’, ‘foodservice’ and ‘mealtimes’, and results show that food qualities, particularly temperature and texture, are important factors impinging on patient satisfaction, and the trolley system of delivery is an acceptable style of service. Service predisposition demonstrates little relevance to patient satisfaction towards overall meal enjoyment. A theoretical model has been developed that identifies hospital foodservice in a cyclic relationship with the community primary healthcare team

Mental workload and driving

International audienceThe aim of this review is to identify the most representative measures of subjective and objective mental workload in driving, and to understand how the subjective and objective levels of mental workload influence the performance as a function of situation complexity and driving experience, i.e., to verify whether the increase of situation complexity and the lack of experience increase the subjective and physiological levels of mental workload and lead to driving performance impairments. This review will be useful to both researchers designing an experimental study of mental workload and to designers of drivers' training content. In the first part, we will broach the theoretical approach with two factors of mental workload and performance, i.e., situation complexity and driving experience. Indeed, a low complex situation (e.g., highways), or conversely a high complex situation (e.g., town) can provoke an overload. Additionally, performing the driving tasks implies producing a high effort for novice drivers who have not totally automated the driving activity. In the second part, we will focus on subjective measures of mental workload. A comparison of questionnaires usually used in driving will allow identifying the most appropriate ones as a function of different criteria. Moreover, we will review the empirical studies to verify if the subjective level of mental workload is high in simple and very complex situations, especially for novice drivers compared to the experienced ones. In the third part, we will focus on physiological measures. A comparison of physiological indicators will be realized in order to identify the most correlated to mental workload. An empirical review will also take the effect of situation complexity and experience on these physiological indicators into consideration. Finally, a more nuanced comparison between subjective and physiological measures will be established from the impact on situation complexity and experience