Curvature pressure in a cosmology with a tired-light redshift

A hypothesis of curvature pressure is used to derive a static and stable cosmology with a tired-light redshift. The idea is that the high energy particles in the inter-galactic medium do not travel along geodesics because of the strong electrostatic forces. The result is a reaction back on the medium that is seen as an additional pressure. Combined with the explanation of the Hubble redshift as a gravitational interaction results in a static and stable cosmology. The predicted Hubble constant is 60.2 km/s/Mpc, the predicted background microwave temperature is 3 degrees and quasar luminosity functions and angular size distributions are shown to be consistent with the model. Since most observations that imply dark matter rely on redshift data it is argued that there is no dark matter. Observations of quasar absorption lines, supernovae light curves and the Butcher-Oemler effect are discussed. The curvature pressure is important for stellar structure and may explain the solar neutrino deficiency.Comment: 27 pages, no figures. This is a rewritten version of astro-ph/9803009 Accepted by Australian J. Phys. Changes to title, typo's and updated reference

Amplitude equations for coupled electrostatic waves in the limit of weak instability

We consider the simplest instabilities involving multiple unstable electrostatic plasma waves corresponding to four-dimensional systems of mode amplitude equations. In each case the coupled amplitude equations are derived up to third order terms. The nonlinear coefficients are singular in the limit in which the linear growth rates vanish together. These singularities are analyzed using techniques developed in previous studies of a single unstable wave. In addition to the singularities familiar from the one mode problem, there are new singularities in coefficients coupling the modes. The new singularities are most severe when the two waves have the same linear phase velocity and satisfy the spatial resonance condition $k_2=2k_1$. As a result the short wave mode saturates at a dramatically smaller amplitude than that predicted for the weak growth rate regime on the basis of single mode theory. In contrast the long wave mode retains the single mode scaling. If these resonance conditions are not satisfied both modes retain their single mode scaling and saturate at comparable amplitudes.Comment: 34 pages (Latex), no figure

RinRuby: Accessing the R Interpreter from Pure Ruby

RinRuby is a Ruby library that integrates the R interpreter in Ruby, making R's statistical routines and graphics available within Ruby. The library consists of a single Ruby script that is simple to install and does not require any special compilation or installation of R. Since the library is 100% pure Ruby, it works on a variety of operating systems, Ruby implementations, and versions of R. RinRuby's methods are simple, making for readable code. This paper describes RinRuby usage, provides comprehensive documentation, gives several examples, and discusses RinRuby's implementation. The latest version of RinRuby can be found at the project website: http://rinruby.ddahl.org/.

FUNNet:a novel biologically-inspired routing algorithm based on fungi

Future data communication networks show three emerging trends: increasing size of networks, increasing traffic volumes and dynamic network topologies. Efficient network management solutions are required that are scalable, can cope with large, and increasing, traffic volumes and provide decentralised and adaptive routing strategies that cope with the dynamics of the network topology. Routing strategies are an important aspect of network management as they have a significant influence on the overall network performance. This paper introduces the preliminary studies for FUNNet, a new routing algorithm inspired by the kingdom of Fungi. Fungi form robust, resilient and responsive networks and these networks change topology as a consequence of changes in local conditions. Fungi are capable of expanding in size as they self-regulate and optimise the balance between exploration and exploitation which is dependent on the transport of the internal resource, i.e. ‘traffic’, within the network. FUNNet exploits the biological processes that are responsible for simulating fungal networks in a bio-inspired routing protocol. The initial results are positive and suggest that fungal metaphors can improve network management, although further evaluation of more complex scenarios is required

Researching the role of the PhD in developing an academic career: does it make a difference?

This single paper builds on the arguments developed through the think piece by Bak (2013) in that it will report on research that explored academics’ experiences of the role of the PhD in developing their academic careers. Bak (2013) questions the ‘conventional way of approaching the PhD´ in South Africa (p.1) and proposes reconsideration of how doctoral education is conceptualised, delivered and valued. The current study, undertaken in Australia and the UK, commenced from the premise that it is commonly assumed that the PhD prepares people for academic careers, yet little is known about how academics are influenced and developed through doctoral study. Early findings demonstrate that the PhD has not been particularly effective in preparing academics for independent research and teaching and that changes in doctoral education are neede

The Segment Ontology: Bridging Music-generic and Domain-specific

Existing semantic representations of music analysis encapsulate narrow sub-domain concepts and are frequently scoped by the context of a particular MIR task. Segmentation is a crucial abstraction in the investigation of phenomena which unfold over time; we present a Segment Ontology as the backbone of an approach that models properties from the musicological domain independently from MIR implementations and their signal processing foundations, whilst maintaining an accurate and complete description of the relationships that link them. This framework provides two principal advantages which are explored through several examples: a layered separation of concerns that aligns the model with the needs of the users and systems that consume and produce the data; and the ability to link multiple analyses of differing types through transforms to and from the Segment axis