2,824 research outputs found
The Reorganisation of Teacher Education in the U.K. and Ontario : Implications for Australia
I visited the U.K. and Ontario in late September and October 1976 to study the reorganization of teacher education which was taking place as a response to a sharp decline in the demand for teachers consequent on a falling birth-rate and a deteriorating economic situation. The main advantage of the study was that it provided a perspective in which the current situation in Australia (and specifically in W.A.) in regard to an \u27over-supply\u27 of teacher education trainees could be more objectively evaluated in a context of common problems. The fact that the problems, particularly in England, are more urgent, complex, critical and of longer standing hopefully means that their attempts to resolve such problems may indicate possible and perhaps profitable directions of change in the Australian situation
Marked improvement in survival among adult Croatian AIDS patients after the introduction of highly active antiretroviral treatment
We compared the survival of patients following the first AIDS event in Croatia from the period 1986-1996 to the period 1997-2000. A total of 72 (81.8%) out of 88 patients from 1986-1996 and 18 (32.1%) out of 56 from 1997-2000 died. Survival following the first AIDS-defining illness markedly improved in the period 1997-2000 compared to the period 1986-1996 (adjusted Hazard Ratio (HR) for patients surviving more than 6 months: 0.11, 95% confidence interval (95% CI) = 0.04-0.29). A CD4+ cell count of < 100 x 10(6)/L was an independent risk factor for patients surviving up to 2 years (adjusted HR = 1.96, 95% CI = 1.1-3.43, p = 0.02). Patients with tuberculosis or fungal infections had a longer survival when compared to other diagnosis (adjusted HR = 0.53, 95% CI = 0.32-0.90, p = 0.01). However, despite dramatic survival benefit of combination antiretroviral therapy, mortality at six months following the first AIDS event was similar in the two study periods and the one-year probability of death was still substantial (27.2%) in the period 1997-2000
Spiking neural network model of reinforcement learning in the honeybee implemented on the GPU
No description supplie
Coarse-grained statistics for attributing criticality to heterogeneous neural networks
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(Quantum) Space-Time as a Statistical Geometry of Lumps in Random Networks
In the following we undertake to describe how macroscopic space-time (or
rather, a microscopic protoform of it) is supposed to emerge as a
superstructure of a web of lumps in a stochastic discrete network structure. As
in preceding work (mentioned below), our analysis is based on the working
philosophy that both physics and the corresponding mathematics have to be
genuinely discrete on the primordial (Planck scale) level. This strategy is
concretely implemented in the form of \tit{cellular networks} and \tit{random
graphs}. One of our main themes is the development of the concept of
\tit{physical (proto)points} or \tit{lumps} as densely entangled subcomplexes
of the network and their respective web, establishing something like
\tit{(proto)causality}. It may perhaps be said that certain parts of our
programme are realisations of some early ideas of Menger and more recent ones
sketched by Smolin a couple of years ago. We briefly indicate how this
\tit{two-story-concept} of \tit{quantum} space-time can be used to encode the
(at least in our view) existing non-local aspects of quantum theory without
violating macroscopic space-time causality.Comment: 35 pages, Latex, under consideration by CQ
GeNN: a code generation framework for accelerated brain simulations
Large-scale numerical simulations of detailed brain circuit models are important for identifying hypotheses on brain functions and testing their consistency and plausibility. An ongoing challenge for simulating realistic models is, however, computational speed. In this paper, we present the GeNN (GPU-enhanced Neuronal Networks) framework, which aims to facilitate the use of graphics accelerators for computational models of large-scale neuronal networks to address this challenge. GeNN is an open source library that generates code to accelerate the execution of network simulations on NVIDIA GPUs, through a flexible and extensible interface, which does not require in-depth technical knowledge from the users. We present performance benchmarks showing that 200-fold speedup compared to a single core of a CPU can be achieved for a network of one million conductance based Hodgkin-Huxley neurons but that for other models the speedup can differ.
GeNN is available for Linux, Mac OS X and Windows platforms. The source code, user manual, tutorials,
Wiki, in-depth example projects and all other related information can be found on the project website http://genn-team.github.io/genn/
A SYNTHETIC GLYCOLIPID WITH B-CELL MITOGENIC ACTIVITY
A synthetic glycolipid, N-palmitoyl-D-glucosamine, (NPG) was found to be a potent B-cell mitogen, that stimulated spleen cells from nu/nu as well as from normal mice. The proper dispersion of the water insoluble preparation is critical for the elicitation of this mitogenic effect. Limulus lysate clotting assay indicated that the NPG preparation either contains only 0.001% endotoxin contamination, or that NPG itself is 10–5 times less active in this assay than purified endotoxic LPS. Since such low levels of endotoxin concentration are not mitogenic, it is concluded that synthetic N-palmitoyl-D-glucosamine, when properly dispersed, is itself a B-cell mitogen
An Inexpensive Flying Robot Design for Embodied Robotics Research
Flying insects are capable of a wide-range of flight and cognitive behaviors which are not currently understood. The replication of these capabilities is of interest to miniaturized robotics, because they share similar size, weight, and energy constraints. Currently, embodiment of insect behavior is primarily done on ground robots which utilize simplistic sensors and have different constraints to flying insects. This limits how much progress can be made on understanding how biological systems fundamentally work. To address this gap, we have developed an inexpensive robotic solution in the form of a quadcopter aptly named BeeBot. Our work shows that BeeBot can support the necessary payload to replicate the sensing capabilities which are vital to bees' flight navigation, including chemical sensing and a wide visual field-of-view. BeeBot is controlled wirelessly in order to process this sensor data off-board; for example, in neural networks. Our results demonstrate the suitability of the proposed approach for further study of the development of navigation algorithms and of embodiment of insect cognition
Diagramming social practice theory:An interdisciplinary experiment exploring practices as networks
Achieving a transition to a low-carbon energy system is now widely recognised as a key challenge facing humanity. To date, the vast majority of research addressing this challenge has been conducted within the disciplines of science, engineering and economics utilising quantitative and modelling techniques. However, there is growing awareness that meeting energy challenges requires fundamentally socio-technical solutions and that the social sciences have an important role to play. This is an interdisciplinary challenge but, to date, there remain very few explorations of, or reflections on, interdisciplinary energy research in practice. This paper seeks to change that by reporting on an interdisciplinary experiment to build new models of energy demand on the basis of cutting-edge social science understandings. The process encouraged the social scientists to communicate their ideas more simply, whilst allowing engineers to think critically about the embedded assumptions in their models in relation to society and social change. To do this, the paper uses a particular set of theoretical approaches to energy use behaviour known collectively as social practice theory (SPT) - and explores the potential of more quantitative forms of network analysis to provide a formal framework by means of which to diagram and visualize practices. The aim of this is to gain insight into the relationships between the elements of a practice, so increasing the ultimate understanding of how practices operate. Graphs of practice networks are populated based on new empirical data drawn from a survey of different types (or variants) of laundry practice. The resulting practice networks are analysed to reveal characteristics of elements and variants of practice, such as which elements could be considered core to the practice, or how elements between variants overlap, or can be shared. This promises insights into energy intensity, flexibility and the rootedness of practices (i.e. how entrenched/ established they are) and so opens up new questions and possibilities for intervention. The novelty of this approach is that it allows practice data to be represented graphically using a quantitative format without being overly reductive. Its usefulness is that it is readily applied to large datasets, provides the capacity to interpret social practices in new ways, and serves to open up potential links with energy modeling. More broadly, a significant dimension of novelty has been the interdisciplinary approach, radically different to that normally seen in energy research. This paper is relevant to a broad audience of social scientists and engineers interested in integrating social practices with energy engineering
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