Estimation of Ocean Surface Currents from Maximum Cross Correlation applied to GOCI geostationary satellite remote sensing data over the Tsushima (Korea) Straits

Attempts to automatically estimate surface current velocities from satellite-derived thermal or visible imagery face the limitations of data occlusion due to cloud cover, the complex evolution of features and the degradation of their surface signature. The Geostationary Ocean Color Imager (GOCI) provides a chance to reappraise such techniques due to its multi-year record of hourly high-resolution visible spectrum data. Here we present the results of applying a Maximum Cross Correlation (MCC) technique to GOCI data. Using a combination of simulated and real data we derive suitable processing parameters and examine the robustness of different satellite products, those being water-leaving radiance and chlorophyll concentration. These estimates of surface currents are evaluated using High Frequency (HF) radar systems located in the Tsushima (Korea) Strait. We show the performance of the MCC approach varies depending on the amount of missing data and the presence of strong optical contrasts. Using simulated data it was found that patchy cloud cover occupying 25% of the image pair reduces the number of vectors by 20% compared to using perfect images. Root mean square errors between the MCC and HF radar velocities are of the order of 20 cm s−1. Performance varies depending on the wavelength of the data with the blue-green products out-performing the red and near infra-red products. Application of MCC to GOCI chlorophyll data results in similar performance to radiances in the blue-green bands. The technique has been demonstrated using specific examples of an eddy feature and tidal induced features in the region. This article is protected by copyright. All rights reserved

Proof Relevant Corecursive Resolution

Resolution lies at the foundation of both logic programming and type class context reduction in functional languages. Terminating derivations by resolution have well-defined inductive meaning, whereas some non-terminating derivations can be understood coinductively. Cycle detection is a popular method to capture a small subset of such derivations. We show that in fact cycle detection is a restricted form of coinductive proof, in which the atomic formula forming the cycle plays the role of coinductive hypothesis. This paper introduces a heuristic method for obtaining richer coinductive hypotheses in the form of Horn formulas. Our approach subsumes cycle detection and gives coinductive meaning to a larger class of derivations. For this purpose we extend resolution with Horn formula resolvents and corecursive evidence generation. We illustrate our method on non-terminating type class resolution problems.Comment: 23 pages, with appendices in FLOPS 201

Exploring multi-sensor satellite synergies to provide direction to high-resolution along-track altimtery currents

A new approach to compute along-track velocity components by combining altimetry-based across-track components and front directions from remote sensing maps of surface chlorophyll concentration is proposed. The analysis focuses on the South Madagascar region characterized by the strong East Madagascar Current and sharp gradients of surface tracers. The results are compared against in-situ observations from three moorings along the Jason-1 track 196. Accurate information on the total velocity direction is the key factor for obtaining accurate estimates of along-track velocities. Although with some limitations, surface tracer fronts can be successfully used to retrieve such information

Towards meta-interpretive learning of programming language semantics

We introduce a new application for inductive logic programming: learning the semantics of programming languages from example evaluations. In this short paper, we explored a simplified task in this domain using the Metagol meta-interpretive learning system. We highlighted the challenging aspects of this scenario, including abstracting over function symbols, nonterminating examples, and learning non-observed predicates, and proposed extensions to Metagol helpful for overcoming these challenges, which may prove useful in other domains.Comment: ILP 2019, to appea

Could Public Restrooms Be an Environment for Bacterial Resistomes?

PMCID: PMC3547874This 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

Fatty acids in bovine milk fat

Milk fat contains approximately 400 different fatty acid, which make it the most complex of all natural fats. The milk fatty acids are derived almost equally from two sources, the feed and the microbial activity in the rumen of the cow and the lipids in bovine milk are mainly present in globules as an oil-in-water emulsion. Almost 70% of the fat in Swedish milk is saturated of which around 11% comprises short-chain fatty acids, almost half of which is butyric acid. Approximately 25% of the fatty acids in milk are mono-unsaturated and 2.3% are poly-unsaturated with omega-6/omega-3 ratio around 2.3. Approximately 2.7% are trans fatty acids

Engaging with assessment: increasing student engagement through continuous assessment

Student engagement is intrinsically linked to two important metrics in learning: student satisfaction and the quality of the student experience. One of the ways that engagement can be influenced is through careful curriculum design. Using the knowledge that many students are ‘assessment-driven’ a low stakes continuous weekly summative e-assessment was introduced to a module. The impact this had on student engagement was measured by studying student activity within the module virtual learning environment (VLE). It was found that introduction of the e-assessments led to a significant increase in VLE activity compared to the VLE activity in that module the previous year, and also compared to the VLE activity of two other modules studied by the same student cohort. As many institutions move towards greater blended or online deliveries it will become more important to ensure that VLEs encourage high levels of student engagement in order to maintain or enhance the student experience. Keywords : continuous assessment, learning analytics, student engagement, virtual learning environment

Adenosine-mono-phosphate-activated protein kinase-independent effects of metformin in T cells

The anti-diabetic drug metformin regulates T-cell responses to immune activation and is proposed to function by regulating the energy-stress-sensing adenosine-monophosphate-activated protein kinase (AMPK). However, the molecular details of how metformin controls T cell immune responses have not been studied nor is there any direct evidence that metformin acts on T cells via AMPK. Here, we report that metformin regulates cell growth and proliferation of antigen-activated T cells by modulating the metabolic reprogramming that is required for effector T cell differentiation. Metformin thus inhibits the mammalian target of rapamycin complex I signalling pathway and prevents the expression of the transcription factors c-Myc and hypoxia-inducible factor 1 alpha. However, the inhibitory effects of metformin on T cells did not depend on the expression of AMPK in T cells. Accordingly, experiments with metformin inform about the importance of metabolic reprogramming for T cell immune responses but do not inform about the importance of AMPK

Genetic architecture of sporadic frontotemporal dementia and overlap with Alzheimer's and Parkinson's diseases

BACKGROUND: Clinical, pathological and genetic overlap between sporadic frontotemporal dementia (FTD), Alzheimer's disease (AD) and Parkinson's disease (PD) has been suggested; however, the relationship between these disorders is still not well understood. Here we evaluated genetic overlap between FTD, AD and PD to assess shared pathobiology and identify novel genetic variants associated with increased risk for FTD. METHODS: Summary statistics were obtained from the International FTD Genomics Consortium, International PD Genetics Consortium and International Genomics of AD Project (n>75 000 cases and controls). We used conjunction false discovery rate (FDR) to evaluate genetic pleiotropy and conditional FDR to identify novel FTD-associated SNPs. Relevant variants were further evaluated for expression quantitative loci. RESULTS: We observed SNPs within the HLA, MAPT and APOE regions jointly contributing to increased risk for FTD and AD or PD. By conditioning on polymorphisms associated with PD and AD, we found 11 loci associated with increased risk for FTD. Meta-analysis across two independent FTD cohorts revealed a genome-wide signal within the APOE region (rs6857, 3′-UTR=PVRL2, p=2.21×10–12), and a suggestive signal for rs1358071 within the MAPT region (intronic=CRHR1, p=4.91×10−7) with the effect allele tagging the H1 haplotype. Pleiotropic SNPs at the HLA and MAPT loci associated with expression changes in cis-genes supporting involvement of intracellular vesicular trafficking, immune response and endo/lysosomal processes. CONCLUSIONS: Our findings demonstrate genetic pleiotropy in these neurodegenerative diseases and indicate that sporadic FTD is a polygenic disorder where multiple pleiotropic loci with small effects contribute to increased disease risk