18 resultados para Term Structure of Interest Rates


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Previously, the Fiji Pneumococcal Project (FiPP) evaluated reduced dose immunization schedules that incorporated pneumococcal protein conjugate and/or polysaccharide vaccine (PCV7 and 23vPPV, respectively). Immune hyporesponsiveness was observed in children vaccinated with 23vPPV at 12 months of age compared with children who did not receive 23vPPV.

Here we assess the long-term impact of 23vPPV vaccination on nasopharyngeal carriage rates and densities of Streptococcus pneumoniae, Haemophilus influenzae, Staphylococcus aureus and Moraxella catarrhalis. Nasopharyngeal swabs (n = 194) were obtained from healthy children who participated in FiPP (now aged 5–7 years). S. pneumoniae were isolated and identified by standard culture-based methods, and serotyped using latex agglutination and the Quellung reaction. Carriage rates and densities of S. pneumoniae, H. influenzae, S. aureus and M. catarrhalis were determined using real-time quantitative PCR.

There were no differences in the rate or density of S. pneumoniae, H. influenzae or M. catarrhalis carriage by PCV7 dose or 23vPPV vaccination in the vaccinated participants overall. However, differences were observed between the two main ethnic groups: Fijian children of Indian descent (Indo-Fijian) were less likely to carry S. pneumoniae, H. influenzae and M. catarrhalis, and there was evidence of a higher carriage rate of S. aureus compared with indigenous Fijian (iTaukei) children. Polysaccharide vaccination appeared to have effects that varied between ethnic groups, with 23vPPV vaccination associated with a higher carriage rate of S. aureus in iTaukei children, while there was a lower carriage rate of S. pneumoniae associated with 23vPPV vaccination in Indo-Fijian children.

Overall, polysaccharide vaccination had no long-term impact on pneumococcal carriage, but may have impacted on S. aureus carriage and have varying effects in ethnic groups, suggesting current WHO vaccine schedule recommendations against the use of 23vPPV in children under two years of age are appropriate.

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As marine management measures increasingly protect static areas of the oceans, it is important to make sure protected areas capture and protect persistent populations. Rocky reefs in many temperate areas worldwide serve as habitat for canopy-forming macroalgae and these structure-forming species of kelps (order Laminariales) often serve as important habitat for a great diversity of species. Macrocystis pyrifera is the most common canopy-forming kelp species found along the coast of California, but the distribution and abundance of M. pyrifera varies in space and time. The purpose of this study is to determine what environmental parameters are correlated with and their relative contribution to the spatial and temporal persistence of M. pyrifera along the central coast of California and how well those environmental parameters can be used to predict areas where this species is more likely to persist. Nine environmental variables considered in this study included depth of the seafloor, structure of the rocky reef, proportion of rocky reef, size of kelp patch, biomass of kelp within a patch, distance from the edge of a kelp patch, sea surface temperature, wave orbital velocities, and population connectivity of individual kelp patches. Using a generalized linear mixed effects model (GLMM), the persistence of M. pyrifera was significantly associated with seven of the nine variables considered: depth, complexity of the rocky reef, proportion of rock, patch biomass, distance from the edge of a patch, population connectivity, and wave orbital velocities. These seven environmental variables were then used to predict the persistence of kelp across the central coast, and these predictions were compared to a reserved dataset of M. pyrifera persistence, which was not used in the creation of the GLMM. The environmental variables were shown to accurately predict the persistence of M. pyrifera within the central coast of California (r = 0.71, P < 0.001). Because persistence of giant kelp is important to the community structure of kelp forests, understanding those factors that support persistent populations of M. pyrifera will enable more effective management of these ecosystems.

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Scale-free networks are often used to model a wide range of real-world networks, such as social, technological, and biological networks. Understanding the structure of scale-free networks evolves into a big data problem for business, management, and protein function prediction. In the past decade, there has been a surge of interest in exploring the properties of scale-free networks. Two interesting properties have attracted much attention: the assortative mixing and community structure. However, these two properties have been studied separately in either theoretical models or real-world networks. In this paper, we show that the structural features of communities are highly related with the assortative mixing in scale-free networks. According to the value of assortativity coefficient, scale-free networks can be categorized into assortative, disassortative, and neutral networks, respectively. We systematically analyze the community structure in these three types of scale-free networks through six metrics: node embeddedness, link density, hub dominance, community compactness, the distribution of community sizes, and the presence of hierarchical communities. We find that the three types of scale-free networks exhibit significant differences in these six metrics of community structures. First, assortative networks present high embeddedness, meaning that many links lying within communities but few links lying between communities. This leads to the high link density of communities. Second, disassortative networks exhibit great hubs in communities, which results in the high compactness of communities that nodes can reach each other via short paths. Third, in neutral networks, a big portion of links act as community bridges, so they display sparse and less compact communities. In addition, we find that (dis)assortative networks show hierarchical community structure with power-law-distributed community sizes, while neutral networks present no hierarchy. Understanding the structure of communities from the angle of assortative mixing patterns of nodes can provide insights into the network structure and guide us in modeling information propagation in different categories of scale-free networks.