Effects of hydrocarbon spills on the temperature and moisture regimes of Cryosols in the Ross Sea region

Hydrocarbon spills have occurred on Antarctic soils where fuel oils are utilized, moved or stored. We investigated the effects of hydrocarbon spills on soil temperature and moisture regimes by comparing the properties of existing oil contaminated sites with those of nearby, uncontaminated, control sites at Scott Base, the old Marble Point camp, and Bull Pass in the Wright Valley. Hydrocarbon levels were elevated in fuel-contaminated samples. Climate stations were installed at all three locations in both contaminated and control sites. In summer at Scott Base and Marble Point the mean weekly maximum near surface (2 cm and 5 cm depth) soil temperatures were warmer (P<0.05), sometimes by more than 10°C, at the contaminated site than the control sites. At Bull Pass there were no statistically significant differences in near-surface soil temperatures between contaminated and control soils. At the Scott Base and Marble Point sites soil albedo was lower, and hydrophobicity was higher, in the contaminated soils than the controls. The higher temperatures at the Scott Base and Marble Point hydrocarbon contaminated sites are attributed to the decreased surface albedo due to soil surface darkening by hydrocarbons. There were no noteworthy differences in moisture retention between contaminated and control sites

A Lightweight Regression Method to Infer Psycholinguistic Properties for Brazilian Portuguese

Psycholinguistic properties of words have been used in various approaches to Natural Language Processing tasks, such as text simplification and readability assessment. Most of these properties are subjective, involving costly and time-consuming surveys to be gathered. Recent approaches use the limited datasets of psycholinguistic properties to extend them automatically to large lexicons. However, some of the resources used by such approaches are not available to most languages. This study presents a method to infer psycholinguistic properties for Brazilian Portuguese (BP) using regressors built with a light set of features usually available for less resourced languages: word length, frequency lists, lexical databases composed of school dictionaries and word embedding models. The correlations between the properties inferred are close to those obtained by related works. The resulting resource contains 26,874 words in BP annotated with concreteness, age of acquisition, imageability and subjective frequency.Comment: Paper accepted for TSD201

A mathematical model for describing the retinal nerve fiber bundle trajectories in the human eye:Average course, variability, and influence of refraction, optic disc size and optic disc position

Previously we developed a mathematical model for describing the retinal nerve fiber bundle trajectories in the superior-temporal and inferior-temporal regions of the human retina, based on traced trajectories extracted from fundus photographs. Aims of the current study were to (i) validate the existing model, (ii) expand the model to the entire retina and (iii) determine the influence of refraction, optic disc size and optic disc position on the trajectories. A new set of fundus photographs was collected comprising 28 eyes of 28 subjects. From these 28 photographs, 625 trajectories were extracted. Trajectories in the temporal region of the retina were compared to the existing model. In this region, 347 of 399 trajectories (87%) were within the 95% central range of the existing model. The model was extended to the nasal region. With this extension, the model can now be applied to the entire retina that corresponds to the visual field as tested with standard automated perimetry (up to approximately 30 eccentricity). There was an asymmetry between the superior and inferior hemifields and a considerable location-specific inter-subject variability. In the nasal region, we found two "singularities", located roughly at the one and five o'clock positions for the right optic disc. Here, trajectories from relatively widespread areas of the retina converge. Associations between individual deviations from the model and refraction, optic disc size and optic disc position were studied with multiple linear regression. Refraction (P = 0.021) and possibly optic disc inclination (P = 0.09) influenced the trajectories in the superior-temporal region. (C) 2012 Elsevier Ltd. All rights reserved

SRflow: Deep learning based super-resolution of 4D-flow MRI data

Exploiting 4D-flow magnetic resonance imaging (MRI) data to quantify hemodynamics requires an adequate spatio-temporal vector field resolution at a low noise level. To address this challenge, we provide a learned solution to super-resolve in vivo 4D-flow MRI data at a post-processing level. We propose a deep convolutional neural network (CNN) that learns the inter-scale relationship of the velocity vector map and leverages an efficient residual learning scheme to make it computationally feasible. A novel, direction-sensitive, and robust loss function is crucial to learning vector-field data. We present a detailed comparative study between the proposed super-resolution and the conventional cubic B-spline based vector-field super-resolution. Our method improves the peak-velocity to noise ratio of the flow field by 10 and 30% for in vivo cardiovascular and cerebrovascular data, respectively, for 4 × super-resolution over the state-of-the-art cubic B-spline. Significantly, our method offers 10x faster inference over the cubic B-spline. The proposed approach for super-resolution of 4D-flow data would potentially improve the subsequent calculation of hemodynamic quantities