Cultural studies and the urgency of interdisciplinarity : sooner, not later, we're going to need a cultural science (Os Estudos Culturais e a urgência por interdisciplinaridade: cedo, e não tarde, vamos precisar de uma Ciência da Cultura)

Most of creativity in the digital world passes unnoticed by the industry practices and policies, and it isn't taken into account in the cultural and economic strategies of the creative industries. We should find ways to catalyze this creative production, showing how the user's contribution may contribute to social learning, cultural and economic advancement. To that effect, we must know what is an open creative system and how it works. Based on this diagnosis, the author that interdisciplinarity is urgent and there is also a need for a science of culture. What is at stake is a strategy of integrated development, as regards the upcoming innovation in its complex, productive and learning aspects.

Specifying peripheral aberrations in visual science

Purpose: Investigations of foveal aberrations assume circular pupils. However, the pupil becomes increasingly elliptical with increase in visual field eccentricity. We address this and other issues concerning peripheral aberration specification. Methods: One approach uses an elliptical pupil similar to the actual pupil shape, stretched along its minor axis to become a circle so that Zernike circular aberration polynomials may be used. Another approach uses a circular pupil whose diameter matches either the larger or smaller dimension of the elliptical pupil. Pictorial presentation of aberrations, influence of wavelength on aberrations, sign differences between aberrations for fellow eyes, and referencing position to either the visual field or the retina are considered. Results: Examples show differences between the two approaches. Each has its advantages and disadvantages, but there are ways to compensate for most disadvantages. Two representations of data are pupil aberration maps at each position in the visual field and maps showing the variation in individual aberration coefficients across the field. Conclusions: Based on simplicity of use, adequacy of approximation, possible departures of off-axis pupils from ellipticity, and ease of understanding by clinicians, the circular pupil approach is preferable to the stretched elliptical approach for studies involving field angles up to 30 deg.

A Bayesian‐Markov process for reliability prediction

Accurate reliability prediction for large-scale, long lived engineering is a crucial foundation for effective asset risk management and optimal maintenance decision making. However, a lack of failure data for assets that fail infrequently, and changing operational conditions over long periods of time, make accurate reliability prediction for such assets very challenging. To address this issue, we present a Bayesian-Marko best approach to reliability prediction using prior knowledge and condition monitoring data. In this approach, the Bayesian theory is used to incorporate prior information about failure probabilities and current information about asset health to make statistical inferences, while Markov chains are used to update and predict the health of assets based on condition monitoring data. The prior information can be supplied by domain experts, extracted from previous comparable cases or derived from basic engineering principles. Our approach differs from existing hybrid Bayesian models which are normally used to update the parameter estimation of a given distribution such as the Weibull-Bayesian distribution or the transition probabilities of a Markov chain. Instead, our new approach can be used to update predictions of failure probabilities when failure data are sparse or nonexistent, as is often the case for large-scale long-lived engineering assets.

PySSM : a Python module for Bayesian inference of linear Gaussian state space models

PySSM is a Python package that has been developed for the analysis of time series using linear Gaussian state space models (SSM). PySSM is easy to use; models can be set up quickly and efficiently and a variety of different settings are available to the user. It also takes advantage of scientific libraries Numpy and Scipy and other high level features of the Python language. PySSM is also used as a platform for interfacing between optimised and parallelised Fortran routines. These Fortran routines heavily utilise Basic Linear Algebra (BLAS) and Linear Algebra Package (LAPACK) functions for maximum performance. PySSM contains classes for filtering, classical smoothing as well as simulation smoothing.

Utilizing argumentation to teach nature of science

The quest for the achievement of informed nature of science (NOS) views for all learners continues to inspire science educators to seek out effective instructional interventions to aid in the development of learners’ NOS views. Despite the extensive amount of research conducted in the field, the development of informed NOS views has been difficult to achieve, with many studies reporting difficulties in changing learners’ NOS views. Can engaging learners in argumentation lead to improvements in their NOS views? This review answers this question by examining studies which have explored NOS and argumentation in science education. The review also outlines a rationale for incorporating argumentation in science education, together with a brief overview of important recent studies in the field. Implications drawn from this review suggest that the incorporation of explicit NOS and argumentation instruction, together with consideration of various contextual, task-specific and personal factors which could mediate learners’ NOS views and engagement in argumentation, could lead to improvements in learners’ views of NOS.

Learning science through real-world contexts

Curriculum developers and researchers have promoted context based programmes to arrest waning student interest and participation in the enabling sciences at high school and university. Context-based programmes aim for connections between scientific discourse and real-world contexts to elevate curricular relevance without diminishing conceptual understanding. Literature relating to context-based approaches to learning will be reviewed in this chapter. In particular, international trends in curricular development and results from evaluations of major projects (e.g. PLON, Salters Advanced Chemistry, ChemCom) will be highlighted. Research projects that explore context-based interventions focusing on such outcomes as student interest, perceived relevance and conceptual understanding also will feature in the review. The chapter culminates with a discussion of current context-based research that interprets classroom actions from a dialectical socio-cultural framework, and identifies possible new directions for research.

Leading the transformation of learning and praxis in science classrooms

Individual science teachers who have inspired colleagues to transform their classroom praxis have been labelled transformational leaders. As the notion of distributed leadership became more accepted in the educational literature, the focus on the individual teacher-leader shifted to the study of leadership praxis both by individuals (whoever they might be) and by collectives within schools and science classrooms. This review traces the trajectory of leadership research, in the context of learning and teaching science, from an individual focus to a dialectical relationship between individual and collective praxis. The implications of applying an individual-collective perspective to praxis for teachers, students and their designated leaders are discussed.

Risk, uncertainty and complexity in science education

Increasingly societies and their governments are facing important social issues that have science and technology as key features. A number of these socio-scientific issues have two features that distinguish them from the restricted contexts in which school science has traditionally been presented. Some of their science is uncertain and scientific knowledge is not the only knowledge involved. As a result, the concepts of uncertainty, risk and complexity become essential aspects of the science underlying these issues. In this chapter we discuss the nature and role of these concepts in the public understanding of science and consider their links with school science. We argue that these same concepts and their role in contemporary scientific knowledge need to be addressed in school science curricula. The new features for content, pedagogy and assessment of this urgent challenge for science educators are outlined. These will be essential if the goal of science education for citizenship is to be achieved with our students, who will increasingly be required to make personal and collective decisions on issues involving science and technology.

A sequential Monte Carlo algorithm to incorporate model uncertainty in Bayesian sequential design

Here we present a sequential Monte Carlo (SMC) algorithm that can be used for any one-at-a-time Bayesian sequential design problem in the presence of model uncertainty where discrete data are encountered. Our focus is on adaptive design for model discrimination but the methodology is applicable if one has a different design objective such as parameter estimation or prediction. An SMC algorithm is run in parallel for each model and the algorithm relies on a convenient estimator of the evidence of each model which is essentially a function of importance sampling weights. Other methods for this task such as quadrature, often used in design, suffer from the curse of dimensionality. Approximating posterior model probabilities in this way allows us to use model discrimination utility functions derived from information theory that were previously difficult to compute except for conjugate models. A major benefit of the algorithm is that it requires very little problem specific tuning. We demonstrate the methodology on three applications, including discriminating between models for decline in motor neuron numbers in patients suffering from neurological diseases such as Motor Neuron disease.

Statistical modelling of wind effects on signal propagation for wireless sensor networks

A wireless sensor network system must have the ability to tolerate harsh environmental conditions and reduce communication failures. In a typical outdoor situation, the presence of wind can introduce movement in the foliage. This motion of vegetation structures causes large and rapid signal fading in the communication link and must be accounted for when deploying a wireless sensor network system in such conditions. This thesis examines the fading characteristics experienced by wireless sensor nodes due to the effect of varying wind speed in a foliage obstructed transmission path. It presents extensive measurement campaigns at two locations with the approach of a typical wireless sensor networks configuration. The significance of this research lies in the varied approaches of its different experiments, involving a variety of vegetation types, scenarios and the use of different polarisations (vertical and horizontal). Non–line of sight (NLoS) scenario conditions investigate the wind effect based on different vegetation densities including that of the Acacia tree, Dogbane tree and tall grass. Whereas the line of sight (LoS) scenario investigates the effect of wind when the grass is swaying and affecting the ground-reflected component of the signal. Vegetation type and scenarios are envisaged to simulate real life working conditions of wireless sensor network systems in outdoor foliated environments. The results from the measurements are presented in statistical models involving first and second order statistics. We found that in most of the cases, the fading amplitude could be approximated by both Lognormal and Nakagami distribution, whose m parameter was found to depend on received power fluctuations. Lognormal distribution is known as the result of slow fading characteristics due to shadowing. This study concludes that fading caused by variations in received power due to wind in wireless sensor networks systems are found to be insignificant. There is no notable difference in Nakagami m values for low, calm, and windy wind speed categories. It is also shown in the second order analysis, the duration of the deep fades are very short, 0.1 second for 10 dB attenuation below RMS level for vertical polarization and 0.01 second for 10 dB attenuation below RMS level for horizontal polarization. Another key finding is that the received signal strength for horizontal polarisation demonstrates more than 3 dB better performances than the vertical polarisation for LoS and near LoS (thin vegetation) conditions and up to 10 dB better for denser vegetation conditions.

Extreme science and engineering : a higher education widening participation initiative at QUT

The QUT Extreme Science and Engineering program provides free hands-on workshops to schools, presented by scientists and engineers to students from prep to year 12 in their own classrooms. The workshops are tied to the school curriculum and give students access to professional quality instruments, helping to stimulate their interest in science and engineering, with the aim of generating a greater take up of STEM related subjects in the senior high school years. In addition to engaging students in activities, workshop presenters provide role models of both genders, helping to breakdown preconceived ideas of the type of person who becomes a scientist or engineer and demystifying the university experience. The Extreme Science and Engineering vans have been running for 10 years and as such demonstrate a sustainable and reproducible model for schools engagement. With funding provided through QUT’s Widening Participation Equity initiative (HEPPP funded) the vans which averaged 120 school visits each year has increased to 150+ visits in 2010. Additionally 100+ workshops (hands-on and career focused) have been presented to students from low socio-economic status schools, on the three QUT campuses in 2011. While this is designed as a long-term initiative the short term results have been very promising, with 3000 students attending the workshops in the first six months and teacher and students feedback has been overwhelmingly positive.

Building the profession together : towards holistic library and information science education

How can a holistic approach to library and information science education encompassing vocational and university sectors that meets the future information workforce requirements be achieved? This paper will outline a twelve month national project that considered this very question. Funded by the Australian Learning and Teaching Council (ALTC).

Living Science: Three years in the Galapagos Islands.

The paper is an outline of work done from 1977-1979 by the authors, as visiting scientists at the Charles Darwin Research Station in the Galapagos Islands, Ecuador.They were funded for three years by the WWF (World Wildlife Fund)and the Bird Preservation Society of UK to study the breeding biology and ethology of Flightless cormorants and the Greater Flamingo. The presentation includes human aspects of living on and travelling between uninhabited islands.

Using approximate Bayesian computation to estimate transmission rates of nosocomial pathogens

In this paper, we apply a simulation based approach for estimating transmission rates of nosocomial pathogens. In particular, the objective is to infer the transmission rate between colonised health-care practitioners and uncolonised patients (and vice versa) solely from routinely collected incidence data. The method, using approximate Bayesian computation, is substantially less computer intensive and easier to implement than likelihood-based approaches we refer to here. We find through replacing the likelihood with a comparison of an efficient summary statistic between observed and simulated data that little is lost in the precision of estimated transmission rates. Furthermore, we investigate the impact of incorporating uncertainty in previously fixed parameters on the precision of the estimated transmission rates.

A behavioural car-following model that captures traffic oscillations

This paper presents a behavioral car-following model based on empirical trajectory data that is able to reproduce the spontaneous formation and ensuing propagation of stop-and-go waves in congested traffic. By analyzing individual drivers’ car-following behavior throughout oscillation cycles it is found that this behavior is consistent across drivers and can be captured by a simple model. The statistical analysis of the model’s parameters reveals that there is a strong correlation between driver behavior before and during the oscillation, and that this correlation should not be ignored if one is interested in microscopic output. If macroscopic outputs are of interest, simulation results indicate that an existing model with fewer parameters can be used instead. This is shown for traffic oscillations caused by rubbernecking as observed in the US 101 NGSIM dataset. The same experiment is used to establish the relationship between rubbernecking behavior and the period of oscillations.