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

Sea ice-ocean coupling during Heinrich Stadials in the Atlantic–Arctic gateway

The variability of Arctic sea-ice during abrupt stadial-interstadial shifts in the last glacial period remain poorly understood. Here, we investigated the millennial-scale relationship, with a focus on Heinrich Stadials (HS), between sea-ice cover and bottom water temperature (BWT) during Marine Isotope Stages (MIS) 3 and 2 (64–13 ka) in the Fram Strait using new molecular sea ice biomarker data and published benthic foraminiferal BWT records. Widespread spring sea-ice cover (SpSIC) dominated the studied interval, especially in mid-late MIS 3 (45–29 ka). Yet, warm interstadials were characterized by relatively more open-ocean conditions compared to cold stadials. At the transition between a HS and the subsequent interstadial, sea ice was tightly linked to BWT with rapid reductions in SpSIC coinciding with lower BWT at the end of HS. The relative timing of the events, especially during HS 1, points to ocean warming as the key controlling factor for sea ice reduction at millennial timescales

Multiple reassortment events in the evolutionary history of H1N1 influenza A virus since 1918

The H1N1 subtype of influenza A virus has caused substantial morbidity and mortality in humans, first documented in the global pandemic of 1918 and continuing to the present day. Despite this disease burden, the evolutionary history of the A/H1N1 virus is not well understood, particularly whether there is a virological basis for several notable epidemics of unusual severity in the 1940s and 1950s. Using a data set of 71 representative complete genome sequences sampled between 1918 and 2006, we show that segmental reassortment has played an important role in the genomic evolution of A/H1N1 since 1918. Specifically, we demonstrate that an A/H1N1 isolate from the 1947 epidemic acquired novel PB2 and HA genes through intra-subtype reassortment, which may explain the abrupt antigenic evolution of this virus. Similarly, the 1951 influenza epidemic may also have been associated with reassortant A/H1N1 viruses. Intra-subtype reassortment therefore appears to be a more important process in the evolution and epidemiology of H1N1 influenza A virus than previously realized

Machine-learning of atomic-scale properties based on physical principles

We briefly summarize the kernel regression approach, as used recently in materials modelling, to fitting functions, particularly potential energy surfaces, and highlight how the linear algebra framework can be used to both predict and train from linear functionals of the potential energy, such as the total energy and atomic forces. We then give a detailed account of the Smooth Overlap of Atomic Positions (SOAP) representation and kernel, showing how it arises from an abstract representation of smooth atomic densities, and how it is related to several popular density-based representations of atomic structure. We also discuss recent generalisations that allow fine control of correlations between different atomic species, prediction and fitting of tensorial properties, and also how to construct structural kernels---applicable to comparing entire molecules or periodic systems---that go beyond an additive combination of local environments

Sea-ice dynamics in an Arctic coastal polynya during the past 6500 years

The production of high-salinity brines during sea-ice freezing in circum-arctic coastal polynyas is thought to be part of northern deep water formation as it supplies additional dense waters to the Atlantic meridional overturning circulation system. To better predict the effect of possible future summer ice-free conditions in the Arctic Ocean on global climate, it is important to improve our understanding of how climate change has affected sea-ice and brine formation, and thus finally dense water formation during the past. Here, we show temporal coherence between sea-ice conditions in a key Arctic polynya (Storfjorden, Svalbard) and patterns of deep water convection in the neighbouring Nordic Seas over the last 6500 years. A period of frequent sea-ice melting and freezing between 6.5 and 2.8 ka BP coincided with enhanced deep water renewal in the Nordic Seas. Near-permanent sea-ice cover and low brine rejection after 2.8 ka BP likely reduced the overflow of high-salinity shelf waters, concomitant with a gradual slow down of deep water convection in the Nordic Seas, which occurred along with a regional expansion in sea-ice and surface water freshening. The Storfjorden polynya sea-ice factory restarted at ~0.5 ka BP, coincident with renewed deep water penetration to the Arctic and climate amelioration over Svalbard. The identified synergy between Arctic polynya sea-ice conditions and deep water convection during the present interglacial is an indication of the potential consequences for ocean ventilation during states with permanent sea-ice cover or future Arctic ice-free conditions

The impact of drinking water, indoor dust and paint on blood lead levels of children aged 1-5 years in Montreal (Quebec, Canada)

Lead is neurotoxic at very low dose and there is a need to better characterize the impact of domestic sources of lead on the biological exposure of young children. A cross-sectional survey evaluated the contribution of drinking water, house dust and paint to blood lead levels (BLLs) of young children living in old boroughs of Montreal (Canada). Three hundred and six children aged 1 to 5 years and currently drinking tap water participated in the study. For each participant, residential lead was measured in kitchen tap water, floor dust, windowsill dust and house paint and a venous blood sample was analyzed. Multivariate logistic regression was used to evaluate the association between elevated BLL in the children (>/= 75th percentile) and indoor lead contamination by means of odds ratios (OR) using 95% confidence intervals (CI). There was an association between BLL >/=75th percentile (1.78 mug/dL) and water lead when the mean water concentration was >3.3 mug/L: adjusted OR=4.7 (95% CI: 2.1-10.2). Windowsill dust loading >14.1 mug/ft(2) was also associated with BLL >/=1.78 mug/dL: adjusted OR=3.2 (95% CI: 1.3-7.8). Despite relatively low BLLs, tap water and house dust lead contribute to an increase of BLLs in exposed young children

Genes Suggest Ancestral Colour Polymorphisms Are Shared across Morphologically Cryptic Species in Arctic Bumblebees

email Suzanne orcd idCopyright: © 2015 Williams et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited