Towards a Flexible Deep Learning Method for Automatic Detection of Clinically Relevant Multi-Modal Events in the Polysomnogram

Much attention has been given to automatic sleep staging algorithms in past years, but the detection of discrete events in sleep studies is also crucial for precise characterization of sleep patterns and possible diagnosis of sleep disorders. We propose here a deep learning model for automatic detection and annotation of arousals and leg movements. Both of these are commonly seen during normal sleep, while an excessive amount of either is linked to disrupted sleep patterns, excessive daytime sleepiness impacting quality of life, and various sleep disorders. Our model was trained on 1,485 subjects and tested on 1,000 separate recordings of sleep. We tested two different experimental setups and found optimal arousal detection was attained by including a recurrent neural network module in our default model with a dynamic default event window (F1 = 0.75), while optimal leg movement detection was attained using a static event window (F1 = 0.65). Our work show promise while still allowing for improvements. Specifically, future research will explore the proposed model as a general-purpose sleep analysis model.Comment: Accepted for publication in 41st International Engineering in Medicine and Biology Conference (EMBC), July 23-27, 201

Managing Resources by Grazing in Grasslands Dominated by Dominant Shrub Species

The European natural grasslands are attracting new attention because of their environmental value as habitats for threatened fauna and flora species and their contribution to the diversity of landscapes. Those responsible for the implementation of the European agri-environmental policy are hence encouraging livestock farmers to adopt grazing practices that contribute to the conservation of grassland biodiversity especially by limiting encroachment by dominant shrubs. However, current scientific knowledge and technical information are often insufficient to connect flock feeding and the impact of grazing on shrub dynamics and livestock farmers are not very enthusiastic about restoring or conserving “plant mosaics” including shrubs that support biodiversity in their fields. This paper presents results of an interdisciplinary study on interactions between small ruminant feeding strategy and population dynamics of dominant shrub species with the objective of managing by grazing the structure of plant community and thus to provide the renewal of resources on a multi-year scale

Development of a semi-automated image-based high-throughput drug screening system.

We previously reported that the innate sensing of the endosymbiont <i>Leishmania</i> RNA virus 1 (LRV1) within <i>Leishmania (Viannia) guyanensis</i> through Toll-like receptor 3, worsens the pathogenesis of parasite infection in mice. The presence of LRV1 has been associated with the failure of first-line treatment in patients infected with LRV1 containing - <i>L. guyanensis</i> and - <i>L. braziliensis</i> parasites. Here, we established a semi-automated image-based high-throughput drug screening (HTDS) protocol to measure parasiticidal activity of the Prestwick chemical library in primary murine macrophages infected with LRV1-containing <i>L. guyanensis</i> . The two-independent screens generated 14 hit compounds with over sixty-nine percent reduction in parasite growth compared to control, at a single dose in both screens. Our screening strategy offers great potential in the search for new drugs and accelerates the discovery rate in the field of drug repurposing against <i>Leishmania</i> . Moreover, this technique allows the concomitant assessment of the effect of drug toxicity on host cell number

How compliance with behavioural measures during the initial phase of a pandemic develops over time: A longitudinal COVID-19 study

In this longitudinal research we adopt a complexity approach to examine temporal dynamics of variables related to compliance with behavioural measures during the COVID-19 pandemic. Dutch participants (N = 2,399) completed surveys with COVID-19-related variables five times over a period of 10 weeks (April 23th – June 30th 2020). With this data we estimated within-person COVID-19 attitude networks containing a broad set of psychological variables and their relations. These networks display variables’ predictive effects over time between measurements and contemporaneous effects during measurements. Results show 1) bidirectional effects between multiple variables relevant for compliance, forming potential feedback loops, and 2) a positive reinforcing structure between compliance, support for behavioural measures, involvement in the pandemic and vaccination intention. These results can explain why levels of these variables decreased throughout the course of the study. The reinforcing structure points towards potentially amplifying effects of interventions on these variables, and might inform processes of polarization. We conclude that adopting a complexity approach might contribute to understanding protective behaviour in the initial phase of pandemics by combining different theoretical models and modelling bidirectional effects between variables. Future research could build upon this research by studying causality with interventions and including additional variables in the networks

New electronic orderings observed in cobaltates under the influence of misfit periodicities

We study with ARPES the electronic structure of CoO2 slabs, stacked with rock-salt (RS) layers exhibiting a different (misfit) periodicity. Fermi Surfaces (FS) in phases with different doping and/or periodicities reveal the influence of the RS potential on the electronic structure. We show that these RS potentials are well ordered, even in incommensurate phases, where STM images reveal broad stripes with width as large as 80\AA. The anomalous evolution of the FS area at low dopings is consistent with the localization of a fraction of the electrons. We propose that this is a new form of electronic ordering, induced by the potential of the stacked layers (RS or Na in NaxCoO2) when the FS becomes smaller than the Brillouin Zone of the stacked structure

High-resolution microwave frequency dissemination on an 86-km urban optical link

We report the first demonstration of a long-distance ultra stable frequency dissemination in the microwave range. A 9.15 GHz signal is transferred through a 86-km urban optical link with a fractional frequency stability of 1.3x10-15 at 1 s integration time and below 10-18 at one day. The optical link phase noise compensation is performed with a round-trip method. To achieve such a result we implement light polarisation scrambling and dispersion compensation. This link outperforms all the previous radiofrequency links and compares well with recently demonstrated full optical links.Comment: 11 pages, 5 figure

TEMPERATURE AND LEVEL DENSITY PARAMETER OF EVAPORATION RESIDUES PRODUCED IN THE REACTION 165Ho + 600 MeV 20Ne

Evaporative and preequilibrium neutrons emitted from evaporation residues in the reaction Ho + 600 MeV neon are exploited to deduce the thermal excitation energy E* and temperature T of the residues. From these quantities the level density parameter is deduced at a temperature of 4.1 MeV

Transcriptional analysis of temporal gene expression in germinating Clostridium difficile 630 endospores.

Clostridium difficile is the leading cause of hospital acquired diarrhoea in industrialised countries. Under conditions that are not favourable for growth, the pathogen produces metabolically dormant endospores via asymmetric cell division. These are extremely resistant to both chemical and physical stress and provide the mechanism by which C. difficile can evade the potentially fatal consequences of exposure to heat, oxygen, alcohol, and certain disinfectants. Spores are the primary infective agent and must germinate to allow for vegetative cell growth and toxin production. While spore germination in Bacillus is well understood, little is known about C. difficile germination and outgrowth. Here we use genome-wide transcriptional analysis to elucidate the temporal gene expression patterns in C. difficile 630 endospore germination. We have optimized methods for large scale production and purification of spores. The germination characteristics of purified spores have been characterized and RNA extraction protocols have been optimized. Gene expression was highly dynamic during germination and outgrowth, and was found to involve a large number of genes. Using this genome-wide, microarray approach we have identified 511 genes that are significantly up- or down-regulated during C. difficile germination (p≤0.01). A number of functional groups of genes appeared to be co-regulated. These included transport, protein synthesis and secretion, motility and chemotaxis as well as cell wall biogenesis. These data give insight into how C. difficile re-establishes its metabolism, re-builds the basic structures of the vegetative cell and resumes growth