1,947 research outputs found

    An ensemble neural network approach for space-time landslide predictive modelling

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    There is an urgent need for accurate and effective Landslide Early Warning Systems (LEWS). Most LEWS are currently based on a single temporally-aggregated measure of rainfall derived from either in-situ measurements or satellite-based rainfall estimates. Relying on a summary metric of precipitation may not capture the complexity of the rainfall signal and its dynamics in space and time in triggering landslides. Here, we present a proof-of-concept for constructing a LEWS that is based on an integrated spatio-temporal modelling framework. Our proposed methodology builds upon a recent approach that uses a daily rainfall time series instead of the traditional cumulated scalar approximation. Specifically, we partition the study area into slope units and use a Gated Recurrent Unit (GRU) to process a satellite-derived rainfall time series and combine the output features with a second neural network (NN) tasked with capturing the effect of terrain characteristics. To assess if our approach enhances accuracy, we applied it in Vietnam and compared it against a standard modelling approach that incorporates terrain characteristics and cumulative rainfall over 14 days. Our protocol leads to better performance in hindcasting landslides when using past rainfall estimates (CHIRPS), as compared to the standard modelling approach. While not tested here, our approach can be extended to rainfall obtained from weather forecasts, potentially leading to actual landslide forecasts

    Loss of CaMKI function disrupts salt aversive learning in C. elegans

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    The ability to adapt behavior to environmental fluctuations is critical for survival of organisms ranging from invertebrates to mammals. Caenorhabditis elegans can learn to avoid sodium chloride when it is paired with starvation. This behavior is likely advantageous to avoid areas without food. While some genes have been implicated in this salt aversive learning behavior, critical genetic components, and the neural circuit in which they act, remain elusive. Here, we show that the sole worm ortholog of mammalian CaMKI/IV, CMK-1, is essential for salt aversive learning behavior in C. elegans. We find that CMK-1 acts in the primary salt-sensing ASE neurons to regulate this behavior. By characterizing the intracellular calcium dynamics in ASE neurons using microfluidics, we find that loss of cmk-1 leads to an altered pattern of sensory- evoked calcium responses that may underlie salt aversive learning. Our study implicates the conserved CaMKI/CMK-1 as an essential cell-autonomous regulator for behavioral plasticity to environmental salt in C. elegans

    Responses to ethanol in C57BL/6 versus C57BL/6 × 129 hybrid mice

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    Although genetic background alters responses to ethanol, there has not yet been a methodical quantification of differences in ethanol-related behaviors between inbred and hybrid mice commonly used in gene-targeting studies. Here, we compared C57BL/6NTac × 129S6/SvEvTac F1 hybrid mice (B6129S6) with C57BL/6NTac inbred mice (B6NT), and C57BL/6J × 129X1/SvJ (B6129X1) and C57BL/6J × 129S4/SvJae F1 hybrids (B6129S4) with C57BL/6J mice (B6J), in five commonly used tests: continuous access two-bottle choice drinking, intermittent limited-access binge drinking, ethanol clearance, ethanol-induced loss of the righting reflex, and conditioned place preference (CPP) for ethanol. We found that inbred B6J and B6NT mice showed greater ethanol preference and consumption than their respective hybrids when ethanol was continuously available. Within the intermittent limited-access drinking procedure, though all lines showed similar intake over eight drinking sessions, the average of all sessions showed that B6NT mice drank significantly more ethanol than B6129S6 mice. In addition, B6J mice consumed more ethanol than B6129X1 mice, although they drank less than B6129S4 mice. No differences in ethanol LORR duration were observed between inbred and hybrid mice. Although ethanol clearance was similar among B6J mice and their respective hybrids, B6NT mice cleared ethanol more rapidly than B6129S6 mice. All lines developed CPP for ethanol. Our findings indicate that it may not be necessary to backcross hybrids to an inbred B6 background to study many ethanol-related behaviors in gene-targeted mice

    Adventures in Supersingularland

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    In this paper, we study isogeny graphs of supersingular elliptic curves. Supersingular isogeny graphs were introduced as a hard problem into cryptography by Charles, Goren, and Lauter for the construction of cryptographic hash functions [CGL06]. These are large expander graphs, and the hard problem is to find an efficient algorithm for routing, or path-finding, between two vertices of the graph. We consider four aspects of supersingular isogeny graphs, study each thoroughly and, where appropriate, discuss how they relate to one another. First, we consider two related graphs that help us understand the structure: the `spine' S\mathcal{S}, which is the subgraph of G(Fp)\mathcal{G}_\ell(\overline{\mathbb{F}_p}) given by the jj-invariants in Fp\mathbb{F}_p, and the graph G(Fp)\mathcal{G}_\ell(\mathbb{F}_p), in which both curves and isogenies must be defined over Fp\mathbb{F}_p. We show how to pass from the latter to the former. The graph S\mathcal{S} is relevant for cryptanalysis because routing between vertices in Fp\mathbb{F}_p is easier than in the full isogeny graph. The Fp\mathbb{F}_p-vertices are typically assumed to be randomly distributed in the graph, which is far from true. We provide an analysis of the distances of connected components of S\mathcal{S}. Next, we study the involution on G(Fp)\mathcal{G}_\ell(\overline{\mathbb{F}_p}) that is given by the Frobenius of Fp\mathbb{F}_p and give heuristics on how often shortest paths between two conjugate jj-invariants are preserved by this involution (mirror paths). We also study the related question of what proportion of conjugate jj-invariants are \ell-isogenous for =2,3\ell = 2,3. We conclude with experimental data on the diameters of supersingular isogeny graphs when =2\ell = 2 and compare this with previous results on diameters of LPS graphs and random Ramanujan graphs.Comment: 46 pages. Comments welcom

    Hierarchical multi-class segmentation of glioma images using networks with multi-level activation function

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    For many segmentation tasks, especially for the biomedical image, the topological prior is vital information which is useful to exploit. The containment/nesting is a typical inter-class geometric relationship. In the MICCAI Brain tumor segmentation challenge, with its three hierarchically nested classes 'whole tumor', 'tumor core', 'active tumor', the nested classes relationship is introduced into the 3D-residual-Unet architecture. The network comprises a context aggregation pathway and a localization pathway, which encodes increasingly abstract representation of the input as going deeper into the network, and then recombines these representations with shallower features to precisely localize the interest domain via a localization path. The nested-class-prior is combined by proposing the multi-class activation function and its corresponding loss function. The model is trained on the training dataset of Brats2018, and 20% of the dataset is regarded as the validation dataset to determine parameters. When the parameters are fixed, we retrain the model on the whole training dataset. The performance achieved on the validation leaderboard is 86%, 77% and 72% Dice scores for the whole tumor, enhancing tumor and tumor core classes without relying on ensembles or complicated post-processing steps. Based on the same start-of-the-art network architecture, the accuracy of nested-class (enhancing tumor) is reasonably improved from 69% to 72% compared with the traditional Softmax-based method which blind to topological prior.Comment: 12pages first versio

    The effectiveness of the 13-valent pneumococcal conjugate vaccine against hypoxic pneumonia in children in Lao People's Democratic Republic: An observational hospital-based test-negative study

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    Background: Pneumococcal pneumonia is a leading cause of childhood mortality. Pneumococcal conjugate vaccines (PCVs) have been shown to reduce hypoxic pneumonia in children. However, there are no studies from Asia examining the effectiveness of PCVs on hypoxic pneumonia. We describe a novel approach to determine the effectiveness of the 13-valent PCV (PCV13) against hypoxia in children admitted with pneumonia in the Lao People's Democratic Republic. Methods: A prospective hospital-based, test-negative observational study of children aged up to 59 months admitted with pneumonia to a single tertiary hospital in Vientiane was undertaken over 54 months. Pneumonia was defined using the 2013 WHO definition. Hypoxia was defined as oxygen saturation <90% in room air or requiring oxygen supplementation during hospitalisation. Test-negative cases and controls were children with hypoxic and non-hypoxic pneumonia, respectively. PCV13 status was determined by written record. Vaccine effectiveness was calculated using logistic regression. Propensity score and multiple imputation analyses were used to handle confounding and missing data. Findings: There were 826 children admitted with pneumonia, 285 had hypoxic pneumonia and 377 were PCV13-vaccinated. The unadjusted, propensity-score adjusted and multiple-imputation adjusted estimates of vaccine effectiveness against hypoxic pneumonia were 23% (95% confidence interval: -9, 46%; p=0•14); 37% (6, 57%; p=0•02) and 35% (7, 55%; p=0•02) respectively. Interpretation: PCV13 is effective against hypoxic pneumonia in Asia, and should be prioritised for inclusion in national immunisation programs. This single hospital-based, test-negative approach can be used to assess vaccine effectiveness in other similar settings. Funding: Funded by the Bill & Melinda Gates Foundation

    Cohort Profile: The Flu Watch Study

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    Influenza is a common, highly contagious respiratory virus which infects all age groups, causing a range of outcomes from asymptomatic infection and mild respiratory disease to severe respiratory disease and death.1 If infected, the adaptive immune system produces a humoral (antibody) and cell-mediated (T cell) immune response to fight the infection.2 Influenza viruses continually evolve through antigenic drift, resulting in slightly different ‘seasonal’ influenza strains circulating each year. Population-level antibody immunity to these seasonal viruses builds up over time, so in any given season only a proportion of the population is susceptible to the circulating strains. Occasionally, influenza A viruses evolve rapidly through antigenic shift by swapping genes with influenza viruses usually circulating in animals. This process creates an immunologically distinct virus to which the population may have little to no antibody immunity. The virus can result in a pandemic if a large portion of the population is susceptible and the virus is easily spread
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