Detecting Delamination via Nonlinear Wave Scattering in a Bonded Elastic Bar

In this paper we examine the effect of delamination on wave scattering, with the aim of creating a control measure for layered waveguides of various bonding types. Previous works have considered specific widths of solitary waves for the simulations, without analysing the effect of changing the soliton parameters. We consider two multi-layered structures: one containing delamination "sandwiched" by perfect bonding and one containing delamination but "sandwiched" by soft bonding. These structures are modelled by coupled Boussinesq-type equations. Matched asymptotic multiple-scale expansions lead to coupled Ostrovsky equations in soft bonded regions and Korteweg-De Vries equations in the perfectly bonded and delaminated region. We use the Inverse Scattering Transform to predict the behaviour in the delaminated regions. In both cases, numerical analysis shows that we can predict the delamination length by changes in the wave structure, and that these changes depend upon the Full Width at Half Magnitude (FWHM) of the incident soliton. In the case of perfect bonding, we derive a theoretical prediction for the change and confirm this numerically. For the soft bonding case, we numerically identify a similar relationship using the change in amplitude. Therefore we only need to compute one curve to determine the behaviour for any incident solitary wave, creating a framework for designing measurement campaigns for rigorously testing the integrity of layered structures.Comment: 12 pages, 7 figure

The Impact Of Aggregating Serogroups In Dynamic Models Of Neisseria Meningitidis Transmission

Background: Neisseria meningitidis (Nm) is a pathogen of multiple serogroups that is highly prevalent in many populations. Serogroups associated with invasive meningococcal disease (IMD) in Canada, for example, include A, B, C, W-135, X and Y. IMD is a rare but serious outcome of Nm infection, and can be prevented with vaccines that target certain serogroups. This has stimulated the development of dynamic models to evaluate vaccine impact. However, these models typically aggregate the various Nm serogroups into a small number of combined groups, instead of modelling each serogroup individually. The impact of aggregation on dynamic Nm model predictions is poorly understood. Our objective was to explore the impact of aggregation on dynamic model predictions. Methods: We developed two age-structured agent-based models-a 2-strain model and a 4-strain model-to simulate vaccination programs in the Canadian setting. The 2-strain model was used to explore two different groupings: C, versus all other serogroups combined; and B, versus all other serogroups combined. The 4-strain model used the four groupings: C, B, Neisseria lactamica, versus all other serogroups combined. We compared the predicted impact of monovalent C vaccine, quadrivalent ACWY vaccine (MCV-4), and monovalent B vaccine (4CMenB) on the prevalence of serogroup carriage under these different models. Results: The 2-strain and 4-strain models predicted similar overall impacts of vaccines on carriage prevalence, especially with respect to the vaccine-targeted serogroups. However, there were some significant quantitative and qualitative differences. Declines in vaccine-targeted serogroups were more rapid in the 2-strain model than the 4-strain model, for both the C and the 4CMenB vaccines. Sustained oscillations, and evidence for multiple attractors (i.e., different types of dynamics for the same model parameters but different initial conditions), occurred in the 4-strain model but not the 2-strain model. Strain replacement was also more pronounced in the 4-strain model, on account of the 4-strain model spreading prevalence more thinly across groups and thus enhancing competitive interactions. Conclusions: Simplifying assumptions like aggregation of serogroups can have significant impacts on dynamic model predictions. Modellers should carefully weigh the advantages and disadvantages of aggregation when formulating models for multi-strain pathogens.Natural Sciences and Engineering Research Council of Canada (NSERC)Canada Foundation for Innovation (CFI

Reduced fetal vitamin D status by maternal undernutrition during discrete gestational windows in sheep

Placental transport of vitamin D and other nutrients (e.g. amino acids, fats and glucose) to the fetus is sensitive to maternal and fetal nutritional cues. We studied the effect of maternal calorific restriction on fetal vitamin D status and the placental expression of genes for nutrient transport (aromatic T-type amino acid transporter-1 [TAT-1]; triglyceride hydrolase / lipoprotein uptake facilitator lipoprotein lipase [LPL]) and vitamin D homeostasis (CYP27B1; vitamin D receptor [VDR]), and their association with markers of fetal cardiovascular function and skeletal muscle growth. Pregnant sheep received 100% total metabolizable energy (ME) requirements (control), 40% total ME requirements peri-implantation (PI40, 1–31 days of gestation [dGA]) or 50% total ME requirements in late gestation (L, 104–127 dGA). Fetal, but not maternal, plasma 25-hydroxy-vitamin D (25OHD) concentration was lower in PI40 and L maternal undernutrition groups (p<0.01) compared with the control group at 0.86 gestation. PI40 group placental CYP27B1 mRNA levels were increased (p<0.05) compared with the control group. Across all groups, higher fetal plasma 25OHD concentration was associated with higher skeletal muscle myofibre and capillary density (p<0.05). In the placenta, higher VDR mRNA levels were associated with higher TAT-1 (p<0.05) and LPL (p<0.01) mRNA levels. In the PI40 maternal undernutrition group only, reduced fetal plasma 25OHD concentration may be mediated in part by altered placental CYP27B1. The association between placental mRNA levels of VDR and nutrient transport genes suggests a way in which the placenta may integrate nutritional cues in the face of maternal dietary challenges and alter fetal physiology

Emergence and spread of drug resistant influenza: A two-population game theoretical model

Background The potential for emergence of antiviral drug resistance during influenza pandemics has raised great concern for public health. Widespread use of antiviral drugs is a significant factor in producing resistant strains. Recent studies show that some influenza viruses may gain antiviral drug resistance without a fitness penalty. This creates the possibility of strategic interaction between populations considering antiviral drug use strategies. Methods To explain why, we develop and analyze a classical 2-player game theoretical model where each player chooses from a range of possible rates of antiviral drug use, and payoffs are derived as a function of final size of epidemic with the regular and mutant strain. Final sizes are derived from a stochastic compartmental epidemic model that captures transmission within each population and between populations, and the stochastic emergence of antiviral drug resistance. High treatment levels not only increase the spread of the resistant strain in the subject population but also affect the other population by increasing the density of the resistant strain infectious individuals due to travel between populations. Results We found two Nash equilibria where both populations treat at a high rate, or both treat at a low rate. Hence the game theoretical analysis predicts that populations will not choose different treatment strategies than other populations, under these assumptions. The populations may choose to cooperate by maintaining a low treatment rate that does not increase the incidence of mutant strain infections or cause case importations to the other population. Alternatively, if one population is treating at a high rate, this will generate a large number of mutant infections that spread to the other population, in turn incentivizing that population to also treat at a high rate. The prediction of two separate Nash equilibria is robust to the mutation rate and the effectiveness of the drug in preventing transmission, but it is sensitive to the volume of travel between the two populations. Conclusions Model-based evaluations of antiviral influenza drug use during a pandemic usually consider populations in isolation from one another, but our results show that strategic interactions could strongly influence a population's choice of antiviral drug use policy. Furthermore, the high treatment rate Nash equilibrium has the potential to become socially suboptimal (i.e. non-Pareto optimal) under model assumptions that might apply under other conditions. Because of the need for players to coordinate their actions, we conclude that communication and coordination between jurisdictions during influenza pandemics is a priority, especially for influenza strains that do not evolve a fitness penalty under antiviral drug resistance.Game theoryStochastic compartmental modelAntiviral drugsDrug resistanceH1N1Fitness penalt

The unusual occurrence of green algal balls of <i>Chaetomorpha linum</i> on a beach in Sydney, Australia.

In spring 2014, thousands of green algal balls were washed up at Dee Why Beach, Sydney, New South Wales, Australia. Reports of algal balls are uncommon in marine systems, and mass strandings on beaches are even more rare, sparking both public and scientific interest. We identified the algal masses as Chaetomorpha linum by using light microscopy and DNA sequencing. We characterize the size and composition of the balls from Dee Why Beach and compare them to previous records of marine algal balls. We describe the environmental conditions that could explain their appearance, given the ecophysiology of C. linum