Deep Metric Learning and Image Classification with Nearest Neighbour Gaussian Kernels

We present a Gaussian kernel loss function and training algorithm for convolutional neural networks that can be directly applied to both distance metric learning and image classification problems. Our method treats all training features from a deep neural network as Gaussian kernel centres and computes loss by summing the influence of a feature's nearby centres in the feature embedding space. Our approach is made scalable by treating it as an approximate nearest neighbour search problem. We show how to make end-to-end learning feasible, resulting in a well formed embedding space, in which semantically related instances are likely to be located near one another, regardless of whether or not the network was trained on those classes. Our approach outperforms state-of-the-art deep metric learning approaches on embedding learning challenges, as well as conventional softmax classification on several datasets.Comment: Accepted in the International Conference on Image Processing (ICIP) 2018. Formerly titled Nearest Neighbour Radial Basis Function Solvers for Deep Neural Network

The Chemistry of Hot Exoplanet Atmospheres: Developing and Applying Chemistry Schemes in 1D and 3D Models

The focus of this work is the development and improvement of chemistry schemes in both 1D and 3D atmosphere models, applied to exoplanets. With an ever increasing number of known exoplanets, planets orbiting stars other than the Sun, the diversity in the physical and chemical nature of planets and their atmospheres is becoming more apparent. One of the prime targets, and the focus of many observational and theoretical studies, are the subclass of exoplanets termed hot Jupiters, Jovian sized planets on very short period orbits around their host star. Due to their close orbit, with orbital periods of just a few days, the atmospheres of such planets are heated to very high temperatures (~1000-2000 K) by the intense irradiation from the star. In addition, it is expected that these planets should have synchronised their rotation with their orbital period, a phenomenon called tidal-locking, that leads to a permanently illuminated dayside and a perpetually dark nightside. This combination of intense heating and tidal-locking leads to an exotic type of atmosphere that is without analogue in our own Solar system. Observational constraints suggest that some of these atmospheres may be clear whilst others may be cloudy or contain haze. Some hot Jupiters appear to be inflated with radii larger than is expected for their mass. For the warmest hot Jupiters optical absorbing species TiO and VO are expected to be present, due to the thermodynamical conditions, where they can strongly influence the thermal structure of the atmosphere, yet so far these species have remained elusive in observations. Theoretical simulations of these planets appear to provide poor matches to the observed emission flux from the nightside of the planet whilst providing a much better agreement with the observed dayside flux. These outstanding questions can be tackled in two complimentary ways. Firstly, the number of exoplanets subject to intense observational scrutiny must be increased to improve the statistical significance of observed trends. Secondly, and in tandem, the suite of available theoretical models applied to such atmospheres must be improved to allow for a more comprehensive understanding of the potential physical and chemical processes that occur in these atmospheres, as well as for better comparison of model predictions with observations. In this thesis we present the development and application of one-dimensional (1D) and three-dimensional (3D) models to the atmospheres of hot exoplanets, with a focus on improving the representation of chemistry. One of the concerns of this work is to couple the radiative transfer and chemistry calculations in a one-dimensional model to allow for a self-consistent model that includes feedback between the chemical composition and the thermal structure. We apply this model to the atmospheres of two typical hot Jupiters to quantify this effect. Implications for previous models that do not include this consistency are discussed. Another major focus is to improve the representation of chemistry in the Met Office Unified Model (UM) for exoplanet applications, a three-dimensional model with its heritage in modelling the Earth atmosphere that has recently been applied to exoplanets. We discuss the coupling of two new chemistry schemes that improve both the flexibility and capabilities of the UM applied to exoplanets. Ultimately these developments will allow for a consistent approach to calculate the 3D chemical composition of the atmosphere taking into account the effect of large scale advection, one of the processes currently hypothesised to cause the discrepancy between model predictions and observations of the nightside emission flux of many hot Jupiters

Temperature-chemistry coupling in the evolution of gas giant atmospheres driven by stellar flares

The effect of enhanced UV irradiation associated with stellar flares on the atmospheric composition and temperature of gas giant exoplanets was investigated. This was done using a 1D radiative-convective-chemical model with self-consistent feedback between the temperature and the non-equilibrium chemistry. It was found that flare-driven changes to chemical composition and temperature give rise to prolonged trends in evolution across a broad range of pressure levels and species. Allowing feedback between chemistry and temperature plays an important role in establishing the quiescent structure of these atmospheres, and determines their evolution due to flares. It was found that cooler planets are more susceptible to flares than warmer ones, seeing larger changes in composition and temperature, and that temperature-chemistry feedback modifies their evolution. Long-term exposure to flares changes the transmission spectra of gas giant atmospheres; these changes differed when the temperature structure was allowed to evolve self-consistently with the chemistry. Changes in spectral features due to the effects of flares on these atmospheres can be associated with changes in composition. The effects of flares on the atmospheres of sufficiently cool planets will impact observations made with JWST. It is necessary to use self-consistent models of temperature and chemistry in order to accurately capture the effects of flares on features in the transmission spectra of cooler gas giants, but this depends heavily on the radiation environment of the planet.Comment: 22 Pages, 22 Figures, Accepted for publication in MNRA

Multimorbidity Content-Based Medical Image Retrieval Using Proxies

Content-based medical image retrieval is an important diagnostic tool that improves the explainability of computer-aided diagnosis systems and provides decision making support to healthcare professionals. Medical imaging data, such as radiology images, are often multimorbidity; a single sample may have more than one pathology present. As such, image retrieval systems for the medical domain must be designed for the multi-label scenario. In this paper, we propose a novel multi-label metric learning method that can be used for both classification and content-based image retrieval. In this way, our model is able to support diagnosis by predicting the presence of diseases and provide evidence for these predictions by returning samples with similar pathological content to the user. In practice, the retrieved images may also be accompanied by pathology reports, further assisting in the diagnostic process. Our method leverages proxy feature vectors, enabling the efficient learning of a robust feature space in which the distance between feature vectors can be used as a measure of the similarity of those samples. Unlike existing proxy-based methods, training samples are able to assign to multiple proxies that span multiple class labels. This multi-label proxy assignment results in a feature space that encodes the complex relationships between diseases present in medical imaging data. Our method outperforms state-of-the-art image retrieval systems and a set of baseline approaches. We demonstrate the efficacy of our approach to both classification and content-based image retrieval on two multimorbidity radiology datasets

Morphology of fluvial networks on Titan: Evidence for structural control

Although Titan’s surface shows clear evidence of erosional modification, such as fluvial incision, evidence for tectonism has been less apparent. On Earth, fluvial networks with strongly preferred orientations are often associated with structural features, such as faults or joints, that influence flow or erodibility. We delineated and classified the morphologies of fluvial drainages on Titan and discovered evidence of structural control. Fluvial networks were delineated both on synthetic aperture radar (SAR) images covering ∼40% of Titan from the Cassini Titan Radar Mapper up through T71 and on visible light images of the Huygens landing site collected by the Descent Imager/Spectral Radiometer (DISR). The delineated networks were assigned to one of three morphologic classes—dendritic, parallel or rectangular—using a quantitative terrestrial drainage pattern classification algorithm modified for use with Titan data. We validated our modified algorithm by applying it to synthetic fluvial networks produced by a landscape evolution model with no structural control of drainage orientations, and confirmed that only a small fraction of the networks are falsely identified as structurally controlled. As a second validation, we confirmed that our modified algorithm correctly classifies terrestrial networks that are classified in multiple previous works as rectangular. Application of this modified algorithm to our Titan networks results in a classification of rectangular for one-half of the SAR and DISR networks. A review of the geological context of the four terrestrial rectangular networks indicates that tensional stresses formed the structures controlling those terrestrial drainages. Based on the similar brittle response of rock and cryogenic ice to stress, we infer that structures formed under tension are the most likely cause of the rectangular Titan networks delineated here. The distribution of these rectangular networks suggests that tensional stresses on Titan may have been widespread.United States. National Aeronautics and Space Administration (NASA Cassini Data Analysis Program Grant NNX08BA81G

Observable signatures of wind-driven chemistry with a fully consistent three dimensional radiative hydrodynamics model of HD 209458b (dataset)

rt_u-as329 - tracer experimentrt_u-as361 - transmission - equilibriumrt_u-as298 - transmission -relaxationrt_u-ar698 - emission - equilibriumrt_u-ar697 - emission - relaxationrt_u-ar586 - relaxationrt_u-ar412 - equilibriumtf_u-ar475 - start from spun up windstf_u-ar354 - resolution 96X60X33 start from spun up windstf_u-ar333 - resolution 72X45X33 start from spun up windstf_u-aq931 - timescale x 1e-8tf_u-aq930 - timescale x 1e-4tf_u-aq815 - resolution 72X45X33tf_u-aq814 - resolution 96X60X33tf-u-aq801 - chemical equilibriumtf_u-aq557 - standard Cooper and Showman 2006tf_u-aq800 - Initialise all carbon in COThe data contained in this submission is associated with the publication Drummond et al, ApJL, 2018.The article associated with this dataset is located in ORE at: http://hdl.handle.net/10871/31897We present a study of the effect of wind-driven advection on the chemical composition of hot Jupiter atmospheres using a fully-consistent 3D hydrodynamics, chemistry and radiative transfer code, the Met Office Unified Model (UM). Chemical modelling of exoplanet atmospheres has primarily been restricted to 1D models that cannot account for 3D dynamical processes. In this work we couple a chemical relaxation scheme to the UM to account for the chemical interconversion of methane and carbon monoxide. This is done consistently with the radiative transfer meaning that departures from chemical equilibrium are included in the heating rates (and emission) and hence complete the feedback between the dynamics, thermal structure and chemical composition. In this letter we simulate the well studied atmosphere of HD 209458b. We find that the combined effect of horizontal and vertical advection leads to an increase in the methane abundance by several orders of magnitude; directly opposite to the trend found in previous works. Our results demonstrate the need to include 3D effects when considering the chemistry of hot Jupiter atmospheres. We calculate transmission and emission spectra, as well as the emission phase curve, from our simulations. We conclude that gas-phase non-equilibrium chemistry is unlikely to explain the model–observation discrepancy in the 4.5 μm Spitzer/IRAC channel. However, we highlight other spectral regions, observable with the James Webb Space Telescope, where signatures of wind-driven chemistry are more prominant.BD and DKS acknowledge funding from the European Research Council (ERC) under the European Unions Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement no. 336792. NJM is part funded by a Leverhulme Trust Research Project Grant. JM and IAB acknowledge the support of a Met Office Academic Partnership secondment. ALC is funded by an STFC studentship. DSA acknowledges support from the NASA Astrobiology Program through the Nexus for Exoplanet System Science. This work used the DiRAC Complexity system, operated by the University of Leicester IT Services, which forms part of the STFC DiRAC HPC Facility. This equipment is funded by BIS National E-Infrastructure capital grant ST/K000373/1 and STFC DiRAC Operations grant ST/K0003259/1. DiRAC is part of the National E-Infrastructure

What do we know about the nexus between culture, age, gender and health literacy? Implications for improving the health and well-being of young Indigenous males

Health literacy, although diversely defined, refers to the abilities, relationships and external environments required for people to successfully promote health. Existing research suggests that health literacy is related to health inequities, including individual and community capacity to navigate health. A diverse range of factors shape health literacy abilities and environments, especially culture, gender and age. However, the nexus between these variables and their cumulative impact on health literacy development remains largely unexplored. Commentary that explores these dynamics among young Indigenous males is particularly scant. In turn, strategies to bridge health equity gaps have been obscured. This article brings together disparate research on health literacy, masculinities, youth studies and men’s health in order to address this oversight. By outlining the collective conceptual contribution of these strands of scholarship, we show that young Indigenous males navigate health literacy through a complex cultural interface that balances both Western and Indigenous understandings of health. Alternative masculine identities, which simultaneously embrace and resist components of hegemonic masculinity, also shape this health literacy lens. We explain that the development of health literacy is important for young people, particularly young Indigenous males, and that this is negotiated in tandem with external support structures, including family and friends. By describing these intersections, we explore the implications for researchers, policymakers and practitioners seeking to achieve the dual goal of improving health literacy and reducing health inequi-ties among this highly marginalised population