Assessing the Health of Richibucto Estuary with the Latent Health Factor Index

The ability to quantitatively assess the health of an ecosystem is often of great interest to those tasked with monitoring and conserving ecosystems. For decades, research in this area has relied upon multimetric indices of various forms. Although indices may be numbers, many are constructed based on procedures that are highly qualitative in nature, thus limiting the quantitative rigour of the practical interpretations made from these indices. The statistical modelling approach to construct the latent health factor index (LHFI) was recently developed to express ecological data, collected to construct conventional multimetric health indices, in a rigorous quantitative model that integrates qualitative features of ecosystem health and preconceived ecological relationships among such features. This hierarchical modelling approach allows (a) statistical inference of health for observed sites and (b) prediction of health for unobserved sites, all accompanied by formal uncertainty statements. Thus far, the LHFI approach has been demonstrated and validated on freshwater ecosystems. The goal of this paper is to adapt this approach to modelling estuarine ecosystem health, particularly that of the previously unassessed system in Richibucto in New Brunswick, Canada. Field data correspond to biotic health metrics that constitute the AZTI marine biotic index (AMBI) and abiotic predictors preconceived to influence biota. We also briefly discuss related LHFI research involving additional metrics that form the infaunal trophic index (ITI). Our paper is the first to construct a scientifically sensible model to rigorously identify the collective explanatory capacity of salinity, distance downstream, channel depth, and silt-clay content --- all regarded a priori as qualitatively important abiotic drivers --- towards site health in the Richibucto ecosystem.Comment: On 2013-05-01, a revised version of this article was accepted for publication in PLoS One. See Journal reference and DOI belo

Magnetic-field-induced charge redistribution in disordered graphene double quantum dots

We have studied the transport properties of a large graphene double quantum dot under the influence of a background disorder potential and a magnetic field. At low temperatures, the evolution of the charge-stability diagram as a function of the B field is investigated up to 10 T. Our results indicate that the charging energy of the quantum dot is reduced, and hence the effective size of the dot increases at a high magnetic field. We provide an explanation of our results using a tight-binding model, which describes the charge redistribution in a disordered graphene quantum dot via the formation of Landau levels and edge states. Our model suggests that the tunnel barriers separating different electron/hole puddles in a dot become transparent at high B fields, resulting in the charge delocalization and reduced charging energy observed experimentally.This work was financially supported by the European GRAND project (ICT/FET, Contract No. 215752) and EPSRC

Detecting hate speech on twitter using a convolution-GRU based deep neural network

In recent years, the increasing propagation of hate speech on social media and the urgent need for effective counter-measures have drawn significant investment from governments, companies, as well as empirical research. Despite a large number of emerging scientific studies to address the problem, existing methods are limited in several ways, such as the lack of comparative evaluations which makes it difficult to assess the contribution of individual works. This paper introduces a new method based on a deep neural network combining convolutional and long short term memory networks, and conducts an extensive evaluation of the method against several baselines and state of the art on the largest collection of publicly available datasets to date. We show that our proposed method outperforms state of the art on 6 out of 7 datasets by between 0.2 and 13.8 points in F1. We also carry out further analysis using automatic feature selection to understand the impact of the conventional manual feature engineering process that distinguishes most methods in this field. Our findings challenge the existing perception of the importance of feature engineering, as we show that: the automatic feature selection algorithm drastically reduces the original feature space by over 90% and selects predominantly generic features from datasets; nevertheless, machine learning algorithms perform better using automatically selected features than the original features

Impaired antibody-mediated protection and defective IgA B cell memory in experimental infection of adults with respiratory syncytial virus

Rationale: Despite relative antigenic stability, respiratory syncytial virus (RSV) re-infects throughout life. After >40 years of research, no effective human vaccine exists and correlates of protection remain poorly defined. Most current vaccine candidates seek to induce high levels of RSV-specific serum neutralizing antibodies, which are associated with reduced RSV-related hospitalization rates in observational studies but may not actually prevent infection. Objectives: Characterize correlates of protection from infection and the generation of RSV-specific humoral memory to promote effective vaccine development. Methods: We inoculated 61 healthy adults with live RSV and studied protection from infection by serum and mucosal antibody. We analyzed RSV-specific peripheral blood plasmablast and memory B cell frequencies and antibody longevity. Measurements and Main Results: Despite moderately high levels of pre-existing serum antibody, 34 (56%) became infected, of whom 23 (68%) developed symptomatic colds. Prior RSV-specific nasal IgA correlated significantly more strongly with protection from PCR-confirmed infection than serum neutralizing antibody. Increases in virus-specific antibody titers were variable and transient in infected subjects, but correlated with plasmablasts that peaked around day 10. During convalescence, only IgG (and no IgA) RSV-specific memory B cells were detectable in peripheral blood. This contrasted with natural influenza infection, where virus-specific IgA memory B cells were readily recovered. Conclusions: This observed specific defect in IgA memory may partly explain RSV's ability to cause recurrent symptomatic infections. If so, vaccines able to induce durable RSV-specific IgA responses may be more protective than those generating systemic antibody alone

Impaired antibody-mediated protection and defective IgA B cell memory in experimental infection of adults with respiratory syncytial virus

Rationale: Despite relative antigenic stability, respiratory syncytial virus (RSV) re-infects throughout life. After >40 years of research, no effective human vaccine exists and correlates of protection remain poorly defined. Most current vaccine candidates seek to induce high levels of RSV-specific serum neutralizing antibodies, which are associated with reduced RSV-related hospitalization rates in observational studies but may not actually prevent infection. Objectives: Characterize correlates of protection from infection and the generation of RSV-specific humoral memory to promote effective vaccine development. Methods: We inoculated 61 healthy adults with live RSV and studied protection from infection by serum and mucosal antibody. We analyzed RSV-specific peripheral blood plasmablast and memory B cell frequencies and antibody longevity. Measurements and Main Results: Despite moderately high levels of pre-existing serum antibody, 34 (56%) became infected, of whom 23 (68%) developed symptomatic colds. Prior RSV-specific nasal IgA correlated significantly more strongly with protection from PCR-confirmed infection than serum neutralizing antibody. Increases in virus-specific antibody titers were variable and transient in infected subjects, but correlated with plasmablasts that peaked around day 10. During convalescence, only IgG (and no IgA) RSV-specific memory B cells were detectable in peripheral blood. This contrasted with natural influenza infection, where virus-specific IgA memory B cells were readily recovered. Conclusions: This observed specific defect in IgA memory may partly explain RSV's ability to cause recurrent symptomatic infections. If so, vaccines able to induce durable RSV-specific IgA responses may be more protective than those generating systemic antibody alone

Exploring deep neural networks for rumor detection

© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. The widespread propagation of numerous rumors and fake news have seriously threatened the credibility of microblogs. Previous works often focused on maintaining the previous state without considering the subsequent context information. Furthermore, most of the early works have used classical feature representation schemes followed by a classifier. We investigate the rumor detection problem by exploring different Deep Learning models with emphasis on considering the contextual information in both directions: forward and backward, in a given text. The proposed system is based on Bidirectional Long Short-Term Memory with Convolutional Neural Network, effectively classifying the tweet into rumors and non-rumors. Experimental results show that the proposed method outperformed the baseline methods with 86.12% accuracy. Furthermore, the statistical analysis also shows the effectiveness of the proposed model than the comparing methods

Validation of Statistical Models for Estimating Hospitalization Associated with Influenza and Other Respiratory Viruses

BACKGROUND: Reliable estimates of disease burden associated with respiratory viruses are keys to deployment of preventive strategies such as vaccination and resource allocation. Such estimates are particularly needed in tropical and subtropical regions where some methods commonly used in temperate regions are not applicable. While a number of alternative approaches to assess the influenza associated disease burden have been recently reported, none of these models have been validated with virologically confirmed data. Even fewer methods have been developed for other common respiratory viruses such as respiratory syncytial virus (RSV), parainfluenza and adenovirus. METHODS AND FINDINGS: We had recently conducted a prospective population-based study of virologically confirmed hospitalization for acute respiratory illnesses in persons <18 years residing in Hong Kong Island. Here we used this dataset to validate two commonly used models for estimation of influenza disease burden, namely the rate difference model and Poisson regression model, and also explored the applicability of these models to estimate the disease burden of other respiratory viruses. The Poisson regression models with different link functions all yielded estimates well correlated with the virologically confirmed influenza associated hospitalization, especially in children older than two years. The disease burden estimates for RSV, parainfluenza and adenovirus were less reliable with wide confidence intervals. The rate difference model was not applicable to RSV, parainfluenza and adenovirus and grossly underestimated the true burden of influenza associated hospitalization. CONCLUSION: The Poisson regression model generally produced satisfactory estimates in calculating the disease burden of respiratory viruses in a subtropical region such as Hong Kong

Effectiveness of guided self-help in decreasing expressed emotion in family caregivers of people diagnosed with depression in Thailand: a randomised controlled trial

Background: High expressed emotion (EE) can extend the duration of illness and precipitate relapse; however, little evidence-based information is available to assist family caregivers of individuals with depression. In the present exploratory study, we examined the effectiveness of a cognitive behaviour therapy (CBT) based guided self-help (GSH) manual in decreasing EE in caregivers of people with depression, in Thailand. Method: A parallel group randomised controlled trial was conducted, following CONSORT guidelines, with 54 caregivers who were allocated equally to GSH or control group (standard outpatient department support). In addition, both groups were contacted weekly by telephone. EE was assessed, using the Family Questionnaire (FQ), at baseline, post-test (Week 8) and follow-up (Week 12). Results: FQ scores at baseline indicated that both groups had similar, though moderately high level of EE. However, between baseline and post-test EE scores decreased markedly in the intervention group, but in contrast, they increased slightly in the control group. Between post-test and follow-up, little change took place in the EE scores of either group. Overall, the intervention group recipients of GSH showed a significant decrease in EE whereas the control group recipients of standard outpatient department support reported a slight increase in EE. Conclusion: These findings provide preliminary evidence that GSH is beneficial in reducing EE in caregivers, which is advantageous to family members with depression and caregivers. The approach may be used as an adjunct to the limited outpatient department support given to caregivers by mental health professionals and, perhaps, to caregivers who do not attend these departments

Ultrahard carbon film from epitaxial two-layer graphene

Atomically thin graphene exhibits fascinating mechanical properties, although its hardness and transverse stiffness are inferior to those of diamond. To date, there hasn't been any practical demonstration of the transformation of multi-layer graphene into diamond-like ultra-hard structures. Here we show that at room temperature and after nano-indentation, two-layer graphene on SiC(0001) exhibits a transverse stiffness and hardness comparable to diamond, resisting to perforation with a diamond indenter, and showing a reversible drop in electrical conductivity upon indentation. Density functional theory calculations suggest that upon compression, the two-layer graphene film transforms into a diamond-like film, producing both elastic deformations and sp2-to-sp3 chemical changes. Experiments and calculations show that this reversible phase change is not observed for a single buffer layer on SiC or graphene films thicker than 3 to 5 layers. Indeed, calculations show that whereas in two-layer graphene layer-stacking configuration controls the conformation of the diamond-like film, in a multilayer film it hinders the phase transformation.Comment: Published online on Nature Nanotechnology on December 18, 201