Hopf bifurcations in multiple-parameter space of the Hodgkin-Huxley equations I. Global organization of bistable periodic solutions

 The Hodgkin-Huxley equations (HH) are parameterized by a number of parameters and shows a variety of qualitatively different behaviors depending on the parameter values. We explored the dynamics of the HH for a wide range of parameter values in the multiple-parameter space, that is, we examined the global structure of bifurcations of the HH. Results are summarized in various two-parameter bifurcation diagrams with I _ext (externally applied DC current) as the abscissa and one of the other parameters as the ordinate. In each diagram, the parameter plane was divided into several regions according to the qualitative behavior of the equations. In particular, we focused on periodic solutions emerging via Hopf bifurcations and identified parameter regions in which either two stable periodic solutions with different amplitudes and periods and a stable equilibrium point or two stable periodic solutions coexist. Global analysis of the bifurcation structure suggested that generation of these regions is associated with degenerate Hopf bifurcations. Received: 23 April 1999 / Accepted in revised form: 24 September 1999     

Skin Commensal Staphylococci May Act as Reservoir for Fusidic Acid Resistance Genes

We analyzed the occurrence and mechanisms of fusidic acid resistance present in staphylococci isolated from 59 healthy volunteers. The fingers of the volunteers were screened for the presence of staphylococci, and the collected isolates were tested for resistance to fusidic acid. A total of 34 fusidic acid resistant staphylococcal strains (all were coagulase-negative) were isolated from 22 individuals (22/59, 37.3%). Examination of the resistance genes revealed that acquired fusB or fusC was present in Staphylococcus epidermidis, Staphylococcus capitis subsp. urealyticus, Staphylococcus hominis subsp. hominis, Staphylococcus warneri and Staphylococcus haemolyticus. Resistance islands (RIs) carrying fusB were found in S. epidermidis and S. capitis subsp. urealyticus, while staphylococcal chromosome cassette (SCC)-related structures harboring fusC were found in S. hominis subsp. hominis. Genotypic analysis of S. epidermidis and S. hominis subsp. hominis indicated that the fus elements were disseminated in diverse genetic strain backgrounds. The fusC elements in S. hominis subsp. hominis strains were highly homologous to SCCfusC in the epidemic sequence type (ST) 239/SCCmecIII methicillin-resistant S. aureus (MRSA) or the pseudo SCCmec in ST779 MRSA. The presence of acquired fusidic acid resistance genes and their genetic environment in commensal staphylococci suggested that the skin commensal staphylococci may act as reservoir for fusidic acid resistance genes.     

Gait Study and Pattern Generation of a Starfish-Like Soft Robot with Flexible Rays Actuated by SMAs

This paper presents the design and development of a starfish-like soft robot with flexible rays and the implementation of multi-gait locomotion using Shape Memory Alloy （SMA） actuators. The design principle was inspired by the starfish, which possesses a remarkable symmetrical structure and soft internal skeleton. A soft robot body was constructed by using 3D printing technology. A kinematic model of the SMA spring was built and developed for motion control according to displacement and force requirements. The locomotion inspired from starfish was applied to the implementation of the multi-ray robot through the flexible actuation induced multi-gait movements in various environments. By virtue of the proposed ray control patterns in gait transition, the soft robot was able to cross over an obstacle approximately twice of its body height. Results also showed that the speed of the soft robot was 6.5 times faster on sand than on a clammy rough terrain. These experiments demonstrated that the bionic soft robot with flexible rays actuated by SMAs and multi-gait locomotion in proposed patterns can perform successfully and smoothly in various terrains.     

The Contribution of Social Behaviour to the Transmission of Influenza A in a Human Population

Variability in the risk of transmission for respiratory pathogens can result from several factors, including the intrinsic properties of the pathogen, the immune state of the host and the host''s behaviour. It has been proposed that self-reported social mixing patterns can explain the behavioural component of this variability, with simulated intervention studies based on these data used routinely to inform public health policy. However, in the absence of robust studies with biological endpoints for individuals, it is unclear how age and social behaviour contribute to infection risk. To examine how the structure and nature of social contacts influenced infection risk over the course of a single epidemic, we designed a flexible disease modelling framework: the population was divided into a series of increasingly detailed age and social contact classes, with the transmissibility of each age-contact class determined by the average contacts of that class. Fitting the models to serologically confirmed infection data from the 2009 Hong Kong influenza A/H1N1p pandemic, we found that an individual''s risk of infection was influenced strongly by the average reported social mixing behaviour of their age group, rather than by their personal reported contacts. We also identified the resolution of social mixing that shaped transmission: epidemic dynamics were driven by intense contacts between children, a post-childhood drop in risky contacts and a subsequent rise in contacts for individuals aged 35–50. Our results demonstrate that self-reported social contact surveys can account for age-associated heterogeneity in the transmission of a respiratory pathogen in humans, and show robustly how these individual-level behaviours manifest themselves through assortative age groups. Our results suggest it is possible to profile the social structure of different populations and to use these aggregated data to predict their inherent transmission potential.