Diagnostics of A Range of Highly Superorbital Carbon Dioxide Flows

Expansion tubes are impulse facilities capable of generating highly energetic hyper-sonic flows. This work surveys a broad range of flow conditions produced in the facility X1 with carbon dioxide test gas, for simulation of spacecraft entry into the Martian atmosphere. Conditions with nominal flow speeds of 7, 9, 11 and 13 km/s were tested. The freestream conditions were calibrated using static/Pitot pressure measurements and advanced optical diagnostics. An extensive set of holographic interferometry experiments was performed on flows over wedges for quantitative study of freestream and post-shock densities, and post-shock ionisation. A one-dimensional code with frozen and equilibrium chemistry capabilities was used to estimate the freestream conditions. An equilibrium chemistry model produced a good match to measured freestream quantities at the high enthalpy conditions which are a major aim of this facility's operation. The freestream in the lower enthalpy conditions was found to be heavily influenced by chemical non-equilibrium. Non-equilibrium in the final unsteady expansion process of flow generation was accounted for by switching from equilibrium to frozen chemistry at a predetermined point. Comparison between the freestream density results of holographic interferometry, pressure measurements and computations shows good agreement.

Evolutionary conservation of the membrane fusion machine

Recent structural studies of proteins mediating membrane fusion reveal intriguing similarities between diverse viral and mammalian systems. Particularly striking is the close similarity between the transmembrane envelope glycoproteins from the retrovirus HTLV-1 and the filovirus Ebola. These similarities suggest similar mechanisms of membrane fusion. The model that fits most currently available data suggests fusion activation in viral systems is driven by a symmetrical conformational change triggered by an activation event such as receptor binding or a pH change. The mammalian vesicle fusion mediated by the SNARE protein complex most likely occurs by a similar mechanism but without symmetry constraints.

A study of the interaction between operator style and machine capability for a hydraulic mining excavator

This paper presents a case study that explores how operator digging style juxtaposes with mechanical capability for a class of hydraulic mining excavators. The relationships between actuator and digging forces are developed and these are used to identify the excavator's capability to apply forces in various directions. Two distinct modes of operation are examined to see how they relate to the mechanical capabilities of the linkage and to establish if one has merit over the other. It is found that one of these styles results in lower loading of the machine.

Electrical and chemical diagnostics of transformers insulation .A. Aged transformer samples

This paper describes the application of two relatively new diagnostic techniques for the determination of insulation condition in aged transformers. The techniques are (a) measurements of interfacial polarization spectra by a DC method and (b) measurements of molecular weight and its distribution by gel permeation chromatography. Several other electrical properties of the cellulose polymer were also investigated. Samples were obtained from a retired power transformer and they were analysed by the developed techniques. Six distribution transformers were also tested with the interfacial polarization spectra measurement technique, and the molecular weight of paper/pressboard samples from these transformers were also measured by the gel permeation chromatography. The variation of the results through different locations in a power transformer is discussed in this paper. The possible correlation between different measured properties was investigated and discussed in this paper.

Electrical and chemical diagnostics of transformers insulation .B. Accelerated aged insulation samples

This paper describes the analysis of accelerated aged insulation samples to investigate the degradation processes observed in the insulation from aged transformers. Short term accelerated ageing experiments were performed on paper wrapped insulated conductors and on pressboard samples. The condition of aged insulation samples was investigated by two relatively new diagnostic techniques: (a) measurements of interfacial polarization spectra by a DC method (b) measurements of molecular weight and its distribution by gel permeation chromatography. Several other electrical properties of the paper/pressboard samples were also studied. Possible correlations have been investigated among the different measured properties. The GPC results have been used to predict how molecular weights change with temperature and time.

Human behaviour modelled as a statistico-deterministic turing machine

'Free will' and its corollary, the concept of individual responsibility are keystones of the justice system. This paper shows that if we accept a physics that disallows time reversal, the concept of 'free will' is undermined by an integrated understanding of the influence of genetics and environment on human behavioural responses. Analysis is undertaken by modelling life as a novel statistico-deterministic version of a Turing machine, i.e. as a series of transitions between states at successive instants of time. Using this model it is proven by induction that the entire course of life is independent of the action of free will. Although determined by prior state, the probability of transitions between states in response to a standard environmental stimulus is not equal to 1 and the transitions may differ quantitatively at the molecular level and qualitatively at the level of the whole organism. Transitions between states correspond to behaviours. It is shown that the behaviour of identical twins (or clones), although determined, would be incompletely predictable and non-identical, creating an illusion of the operation of 'free will'. 'Free will' is a convenient construct for current judicial systems and social control because it allows rationalization of punishment for those whose behaviour falls outside socially defined norms. Indeed, it is conceivable that maintenance of ideas of free will has co-evolved with community morality to reinforce its operation. If the concept is free will is to be maintained it would require revision of our current physical theories.

Predictive vaccinology: Optimisation of predictions using support vector machine classifiers

Promiscuous human leukocyte antigen (HLA) binding peptides are ideal targets for vaccine development. Existing computational models for prediction of promiscuous peptides used hidden Markov models and artificial neural networks as prediction algorithms. We report a system based on support vector machines that outperforms previously published methods. Preliminary testing showed that it can predict peptides binding to HLA-A2 and -A3 super-type molecules with excellent accuracy, even for molecules where no binding data are currently available.

Applying machine learning to catalogue matching in astrophysics

We present the results of applying automated machine learning techniques to the problem of matching different object catalogues in astrophysics. In this study, we take two partially matched catalogues where one of the two catalogues has a large positional uncertainty. The two catalogues we used here were taken from the H I Parkes All Sky Survey (HIPASS) and SuperCOSMOS optical survey. Previous work had matched 44 per cent (1887 objects) of HIPASS to the SuperCOSMOS catalogue. A supervised learning algorithm was then applied to construct a model of the matched portion of our catalogue. Validation of the model shows that we achieved a good classification performance (99.12 per cent correct). Applying this model to the unmatched portion of the catalogue found 1209 new matches. This increases the catalogue size from 1887 matched objects to 3096. The combination of these procedures yields a catalogue that is 72 per cent matched.

Extreme learning machine for predicting HLA-peptide binding

Machine learning techniques have been recognized as powerful tools for learning from data. One of the most popular learning techniques, the Back-Propagation (BP) Artificial Neural Networks, can be used as a computer model to predict peptides binding to the Human Leukocyte Antigens (HLA). The major advantage of computational screening is that it reduces the number of wet-lab experiments that need to be performed, significantly reducing the cost and time. A recently developed method, Extreme Learning Machine (ELM), which has superior properties over BP has been investigated to accomplish such tasks. In our work, we found that the ELM is as good as, if not better than, the BP in term of time complexity, accuracy deviations across experiments, and most importantly - prevention from over-fitting for prediction of peptide binding to HLA.

Using machine vision classification to control access of animals to water

Invasive vertebrate pests together with overabundant native species cause significant economic and environmental damage in the Australian rangelands. Access to artificial watering points, created for the pastoral industry, has been a major factor in the spread and survival of these pests. Existing methods of controlling watering points are mechanical and cannot discriminate between target species. This paper describes an intelligent system of controlling watering points based on machine vision technology. Initial test results clearly demonstrate proof of concept for machine vision in this application. These initial experiments were carried out as part of a 3-year project using machine vision software to manage all large vertebrates in the Australian rangelands. Concurrent work is testing the use of automated gates and innovative laneway and enclosure design. The system will have application in any habitat throughout the world where a resource is limited and can be enclosed for the management of livestock or wildlife.