Enhanced detectability of community structure in multilayer networks through layer aggregation

Many systems are naturally represented by a multilayer network in which edges exist in multiple layers that encode different, but potentially related, types of interactions, and it is important to understand limitations on the detectability of community structure in these networks. Using random matrix theory, we analyze detectability limitations for multilayer (specifically, multiplex) stochastic block models (SBMs) in which L layers are derived from a common SBM. We study the effect of layer aggregation on detectability for several aggregation methods, including summation of the layers' adjacency matrices for which we show the detectability limit vanishes as O(L^{-1/2}) with increasing number of layers, L. Importantly, we find a similar scaling behavior when the summation is thresholded at an optimal value, providing insight into the common - but not well understood - practice of thresholding pairwise-interaction data to obtain sparse network representations.Comment: 7 pages, 4 figure

The development of a new sport-specific classification of coping and a meta-analysis of the relationship between different coping strategies and moderators on sporting outcomes

There is an ever growing coping and sports performance literature, with researchers using many different methods to assess performance and different classifications of coping. As such, it makes it difficult to compare studies and therefore identify how coping is related to performance. Furthermore, there are no quantitative syntheses of the results from these studies. A quantitative synthesis would facilitate a more comprehensive understanding of how coping is associated with athletic performance. In order to accurately compare studies, our first aim was to develop a new coping classification that would make this possible. Firstly, we reviewed the strengths and limitations of the different coping classifications and then identified the commonalities and differences between such classifications. We opted for a three-factor classification of coping, because the evidence suggests that a three-factor classification provides a superior model fit to two-factor approaches. Our new classification of coping was based on an existing model from the developmental literature, which received an excellent model fit. We made some adaptations, however, as our classification was intended for an athletic population. As such, we classified coping as mastery (i.e., controlling the situation and eliminating the stressor), internal regulation (i.e., managing internal stress responses), or goal withdrawal (i.e., ceasing efforts towards goal attainment). Undertaking a meta-analysis, our second aim was to identify which coping strategies correlated with sports performance and whether this relationship varied according to moderator variables. Articles were sourced from online electronic databases and manual journal searches. PRISMA guidelines were used to search, select, and synthesize relevant studies. Random effects meta-analyses were performed to identify associations between coping classification and sport performance. Q, I2, and R2 values assessed heterogeneity. Eighteen published investigations, including 3900 participants and incorporating fifty-nine correlations, indicated an overall positive effect for mastery coping, a negligible negative effect for internal regulation coping, and a negative effect for goal withdrawal strategies. The findings of this meta-analysis could be used by sports practitioners to help them deliver effective coping interventions. In order to maximize performance, practitioners could encourage the use of mastery coping, but advise their athletes not to use goal withdrawal strategies

Enhanced Detectability of Community Structure in Multilayer Networks through Layer Aggregation

Many systems are naturally represented by a multilayer network in which edges exist in multiple layers that encode different, but potentially related, types of interactions, and it is important to understand limitations on the detectability of community structure in these networks. Using random matrix theory, we analyze detectability limitations for multilayer (specifically, multiplex) stochastic block models (SBMs) in which L layers are derived from a common SBM. We study the effect of layer aggregation on detectability for several aggregation methods, including summation of the layers’ adjacency matrices for which we show the detectability limit vanishes as (L−1/2) with increasing number of layers, L. Importantly, we find a similar scaling behavior when the summation is thresholded at an optimal value, providing insight into the common—but not well understood—practice of thresholding pairwise-interaction data to obtain sparse network representations

The use of mitochondrial DNA for the identification of fish in the early stages of development from the eastern shores of Lake Huron, Ontario, Canada

Ichthyoplankton specimens are notoriously difficult to identify using morphology. DNA barcoding and real-time PCR utilize DNA to identify specimens, rather than morphology. However, no study has yet compared morphological identifications with DNA-based identification for Canadian freshwater fishes. Here, we both compare DNA barcoding with morphological identification of ichthyoplankton and design a multiplex TaqMan real-time PCR assay for the rapid and cost-effective identification of 3 important species in Lake Huron, lake whitefish (Coregonus clupeaformis), deepwater sculpin (Myoxocephalus thompsonii) and round whitefish (Prosopium cylindraceum). Unlike morphological identification, DNA barcoding was able to resolve specimens from the Catostomus genus and Cyprinidae family to the species. Contrarily, DNA barcoding was unable to differentiate some members of the Coregonus genus, whereas morphology identified these specimens to the species. Real-time PCR was able to accurately identify the target species 100% of the time and was the most cost-effective method.Master of Science (MSc) in Biolog

Speech-language Pathology Services Delivered by Telehealth in a Rural Educational Setting: the School’s Perspective

Introduction: Access to speech-language pathology services for children in rural and remote communities is often limited. Telehealth is increasingly used to provide these services to schools, demonstrating high satisfaction with both service providers and recipients, but the requirements for successful program implementation are as yet unclear. We aimed to explore the implementation requirements for a telehealth speech-language pathology service for children from the perspective of a rural school. Methods: A qualitative approach, supplemented by program activity data, was used to understand the experiences and perceptions of the benefits, limitations, enablers and barriers of a telehealth speech-language pathology program delivered to a school servicing approximately 400 children in a small rural town in the state of Queensland, Australia. Thematic analysis was conducted of transcripts of individual semi-structured interviews with nine school teaching staff and field notes of informal discussions regarding 85 speech-language pathology telehealth sessions (n = 9 children) during program establishment and implementation. Results: The speech-language pathology telehealth service was acceptable to teaching staff at the rural school, who cited improved access, the suitability of the technology for child engagement, and perceived effectiveness. Implementation issues were highlighted as critical to program success and scalability, particularly staff workload, technological issues, communication processes, and sustainability. Conclusion: School-based speech-language pathology services delivered via telehealth were perceived as a suitable way of increasing access for children by rural school staff. Future implementations of telehealth speech-language pathology programs should prospectively consider workload implications and develop strategies to communicate with and involve school staff.     &nbsp

The impact of asking intention or self-prediction questions on subsequent behavior: a meta-analysis

The current meta-analysis estimated the magnitude of the impact of asking intention and self-prediction questions on rates of subsequent behavior, and examined mediators and moderators of this question–behavior effect (QBE). Random-effects meta-analysis on 116 published tests of the effect indicated that intention/prediction questions have a small positive effect on behavior (d+ = 0.24). Little support was observed for attitude accessibility, cognitive dissonance, behavioral simulation, or processing fluency explanations of the QBE. Multivariate analyses indicated significant effects of social desirability of behavior/behavior domain (larger effects for more desirable and less risky behaviors), difficulty of behavior (larger effects for easy-to-perform behaviors), and sample type (larger effects among student samples). Although this review controls for co-occurrence of moderators in multivariate analyses, future primary research should systematically vary moderators in fully factorial designs. Further primary research is also needed to unravel the mechanisms underlying different variants of the QBE

The impact of ensemble meteorology on inverse modeling estimates of volcano emissions and ash dispersion forecasts: Grímsvötn 2011

Volcanic ash can interact with the earth system on many temporal and spatial scales and is a significant hazard to aircraft. In the event of a volcanic eruption, fast and robust decisions need to be made by aviation authorities about which routes are safe to operate. Such decisions take into account forecasts of ash location issued by Volcanic Ash Advisory Centers (VAACs) which are informed by simulations from Volcanic Ash Transport and Dispersion (VATD) models. The estimation of the time-evolving vertical distribution of ash emissions for use in VATD simulations in real time is difficult which can lead to large uncertainty in these forecasts. This study presents a method for constraining the ash emission estimates by combining an inversion modeling technique with an ensemble of meteorological forecasts, resulting in an ensemble of ash emission estimates. These estimates of ash emissions can be used to produce a robust ash forecast consistent with observations. This new ensemble approach is applied to the 2011 eruption of the Icelandic volcano Grímsvötn. The resulting emission profiles each have a similar temporal evolution but there are differences in the magnitude of ash emitted at different heights. For this eruption, the impact of precipitation uncertainty (and the associated wet deposition of ash) on the estimate of the total amount of ash emitted is larger than the impact of the uncertainty in the wind fields. Despite the differences that are dominated by wet deposition uncertainty, the ensemble inversion provides confidence that the reduction of the unconstrained emissions (a priori), particularly above 4 km, is robust across all members. In this case, the use of posterior emission profiles greatly reduces the magnitude and extent of the forecast ash cloud. The ensemble of posterior emission profiles gives a range of ash column loadings much closer in agreement with a set of independent satellite retrievals in comparison to the a priori emissions. Furthermore, airspace containing volcanic ash concentrations deemed to be associated with the highest risk (likelihood of exceeding a high concentration threshold) to aviation are reduced by over 85%. Such improvements could have large implications in emergency response situations. Future research will focus on quantifying the impact of uncertainty in precipitation forecasts on wet deposition in other eruptions and developing an inversion system that makes use of the state-of-the-art meteorological ensembles which has the potential to be used in an operational setting

Neighbourhood unemployment and other socio-demographic predictors of emergency hospitalisation for infectious intestinal disease in England: A longitudinal ecological study

BACKGROUND:Previous studies have observed that infectious intestinal disease (IID) related hospital admissions are higher in more deprived neighbourhoods. These studies have mainly focused on paediatric populations and are cross-sectional in nature. This study examines recent trends in emergency IID admission rates, and uses longitudinal methods to investigate the effects of unemployment (as a time varying measure of neighbourhood deprivation) and other socio-demographic characteristics on IID admissions for adults and children in England. METHODS:A longitudinal ecological analysis was performed using Hospital Episode Statistics on emergency hospitalisations for IID, collected over the time period 2012-17 across England. Analysis was conducted at the neighbourhood (Lower-layer Super Output Area) level for three age groups (0-14; 15-64; 65+ years). Mixed-effect Poisson regression models were used to assess the relationship between trends in neighbourhood unemployment and emergency IID admission rates, whilst controlling for measures of primary and secondary care access, underlying morbidity and the ethnic composition of each neighbourhood. RESULTS:From 2012-17, declining trends in emergency IID admission rates were observed for children and older adults overall, while rates increased for some sub-groups in the population. Each 1 percentage point increase in unemployment was associated with a 6.3, 2.4 and 4% increase in the rate of IID admissions per year for children [IRR=1.06, 95%CI 1.06-1.07], adults [IRR=1.02, 95%CI 1.02-1.03] and older adults [IRR=1.04, 95%CI 1.036-1.043], respectively. Increases in poor primary care access, the percentage of people from a Pakistani ethnic background, and the prevalence of long-term health problems, in a neighbourhood, were also associated with increases in IID admission rates. CONCLUSIONS:Increasing trends in neighbourhood deprivation, as measured by unemployment, were associated with increases in emergency IID admission rates for children and adults in England, despite controlling for measures of healthcare access, underlying morbidity and ethnicity. Research is needed to improve understanding of the mechanisms that explain these inequalities, so that effective policies can be developed to reduce the higher emergency IID admission rates experienced by more disadvantaged communities