It makes you realize, really, just how deep your subtext is : Literature, subjectivity and curriculum change

This paper draws on the notion of discourse to explore complex relationships between teachers and curriculum change. It uses poststructuralist views of discourse to explore ways in which school subjects, such as Literature, are discursively constructed across time, while teachers too are positioned within discourses that shape the ways they understand the subject and themselves as teachers of it. This paper reports on the experience of a small group of teachers of a new literature course in the Australian state of Victoria. Nine teachers were interviewed over 3 years, and the interview transcripts read for traces of discourses formative in shaping their response to the new course. I identified three discourses: Leavisite and New Critical formations of the subject Literature; charismatic pedagogy; and critical theory, which was embodied in the new subject's study design. These 3 discourses, together with the traditions and culture of the school, form the framework for analysis of the interviews. The paper explores ways in which the teachers' positioning within this mix of discourses and settings variously supported or undermined their preparedness to accept new configurations of the subject Literature as well as the implications of curriculum change not just for constructions of the subject but also for teacher subjectivity.

Haptic guidance for microrobotic intracellular injection

The ability for a bio-operator to utilise a haptic device to manipulate a microrobot for intracellular injection offers immense benefits. One significant benefit is for the bio-operator to receive haptic guidance while performing the injection process. In order to address this, this paper investigates the use of haptic virtual fixtures for cell injection and proposes a novel force field virtual fixture. The guidance force felt by the bio-operator is determined by force field analysis within the virtual fixture. The proposed force field virtual fixture assists the bio-operator when performing intracellular injection by limiting the micropipette tip's motion to a conical volume as well as recommending the desired path for optimal injection. A virtual fixture plane is also introduced to prevent the bio-operator from moving the micropipette tip beyond the deposition target inside the cell. Simulation results demonstrate the operation of the guidance system.

Haptic microrobotic intracellular injection assistance using virtual fixtures

In manual cell injection the operator relies completely on visual information for task feedback and is subject to extended training times as well as poor success rates and repeatability. From this perspective, enhancing human-in-the-loop intracellular injection through haptic interaction offers significant benefits. This paper outlines two haptic virtual fixtures aiming to assist the human operator while performing cell injection. The first haptic virtual fixture is a parabolic force field designed to assist the operator in guiding the micropipette's tip to a desired penetration point on the cell's surface. The second is a planar virtual fixture which attempts to assist the operator from moving the micropipette's tip beyond the deposition target location inside the cell. Preliminary results demonstrate the operation of the haptically assisted microrobotic cell injection system.

Mathematical modelling of deep bed filtration

Numerous mathematical models have been developed to evaluate both initial and transient stage removal efficiency of deep bed filters. Microscopic models either using trajectory analysis or convective-diffusion equations were used to compute the initial removal efficiency. These models predicted the removal efficiency under favorable filtration conditions quantitatively, but failed to predict the removal efficiency under unfavorable conditions. They underestimated the removal efficiency under unfavorable conditions. Thus, semi-empirical formulations were developed to compute initial removal efficiencies under unfavorable conditions. Also, correction for the adhesion of particles onto filter grains improved the results obtained for removal efficiency from the trajectory analysis. Macroscopic models were used to predict the transient stage removal efficiency of deep bed filters. O’Melia and Ali’s model assumed that the particle removal is due to filter grains as well as the particles that are already deposited onto the filter grain. Thus, semi-empirical models were used to predict the ripening of filtration. Several modifications were made to the model developed by O’Melia and Ali to predict the deterioration of particle removal during the transient stages of filtration. Models considering the removal of particles under favorable conditions and the accumulation of charges on the filter grains during the transient stages were also developed. This paper evaluates those models and their applicability under different operating conditions of filtration.

Deep bed filtration : mathematical models and observations

Numerous mathematical models have been developed to evaluate both initial and transient stage removal efficiency of deep bed filters. Microscopic models either using trajectory analysis or convective diffusion equations were used to compute the initial removal efficiency. These models predicted the removal efficiency under favorable filtration conditions quantitatively, but failed to predict the removal efficiency under unfavorable conditions. They underestimated the removal efficiency under unfavorable conditions. Thus, semi-empirical formulations were developed to compute initial removal efficiencies under unfavorable conditions. Also, correction for the adhesion of particles onto filter grains improved the results obtained for removal efficiency from the trajectory analysis. Macroscopic models were used to predict the transient stage removal efficiency of deep bed filters. The O’Melia and Ali1 model assumed that the particle removal is due to filter grains as well as the particles that are already deposited onto the filter grain. Thus, semi-empirical models were used to predict the ripening of filtration. Several modifications were made to the model developed by O’Melia and Ali to predict the deterioration of particle removal during the transient stages of filtration. Models considering the removal of particles under favorable conditions and the accumulation of charges on the filter grains during the transient stages were also developed. This article evaluates those models and their applicability under different operating conditions of filtration.

3D particle-based cell modelling for haptic microrobotic cell injection

Introducing haptic interface to conduct microrobotic intracellular injection has many beneficial implications. In particular, the haptic device provides force feedback to the bio-operator's hand. This paper introduces a 3D particle-based model to simulate the deformation of the cell membrane and corresponding cellular forces during microrobotic cell injection. The model is based on the kinematic and dynamic of spring – damper multi particle joints considering visco-elastic fluidic properties. It simulates the indentation force feedback as well as cell visual deformation during the microinjection. The model is verified using experimental data of zebrafish embryo microinjection. The results demonstrate that the developed cell model is capable of estimating zebrafish embryo deformation and force feedback accurately.

Deep in the desert: merging the desert and the spiritual through 4WD tourism

Our paper positions four-wheel drive (4WD) travel into the Australian desert by veteran or dedicated travellers as a spiritual experience in three ways: by considering the desert itself as a sacred space; the experience of such a journey as a form of ‘nature religion’; and by viewing the actual journey itself as pilgrimage. Our argument is informed by interviews with expert 4WDers to the desert. Our study might be useful in designing sustainable strategies for 4WD desert tourism, as well as for scholars from a variety of disciplines such as sustainability and environment studies, religious studies and tourism studies, to name a few.

Defence against code injection attacks

Code injection attacks are considered serious threats to the Internet users. In this type of attack the attacker injects malicious codes in the user programs to change or divert the execution flows. In this paper we explore the contemporary defence strategies against code injection attacks (CIAs) and underline their limitations. To overcome these limitations, we suggest a number of countermeasure mechanisms for protecting from CIAs. Our key idea relies on the multiplexing technique to preserve the exact return code to ensure the integrity of program execution trace of shell code. This technique also maintains a FIFO (first in first out) queue to defeat the conflict state when multiple caller method makes a call simultaneously. Finally, our technique can provide better performance, in terms of protection and speed, in some point compared to the CFI (control flow integrity) as well as CPM (code pointer masking) techniques.

Qualitative assessment of bubble behaviour for central and asymmetric injection in 2D gas-solid fluidized bed using image analysis technique and CFD modelling

Bubble characteristics such as shape, size, and trajectory control the hydrodynamics and therefore heat transfer in fluidized bed reactors. Thus understanding these characteristics is very important for the design and scaleup of fluidized beds. An earlier developed Eulerian-Eulerian two-fluid model for simulating dense gas–solid two-phase flow has been used to compare the experimental data in a pseudo-two-dimensional (2-D) bed. Bubbles are injected asymmetrically by locating the nozzle at proximity to the wall, thus presenting the effect wall has on asymmetrical injection as compared to symmetrical injection. In this work, a digital image analysis technique was developed to study the bubble behaviour in a two-dimensional bubbling bed. The high-speed photography reveals an asymmetric wake formation during detachment indicating an early onset of mixing process. The wall forces acts tangentially on thebubble and has a significant impact on the bubble shape, neck formation during detachment and its trajectory through the bed. Larger bubbles drifting away from the centre with longer paths are observed. This qualitative behaviour is well predicted by CFD modelling. Asymmetric injection can significantly influence the heat and mass transfer characteristics.

High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning

High-dimensional problem domains pose significant challenges for anomaly detection. The presence of irrelevant features can conceal the presence of anomalies. This problem, known as the '. curse of dimensionality', is an obstacle for many anomaly detection techniques. Building a robust anomaly detection model for use in high-dimensional spaces requires the combination of an unsupervised feature extractor and an anomaly detector. While one-class support vector machines are effective at producing decision surfaces from well-behaved feature vectors, they can be inefficient at modelling the variation in large, high-dimensional datasets. Architectures such as deep belief networks (DBNs) are a promising technique for learning robust features. We present a hybrid model where an unsupervised DBN is trained to extract generic underlying features, and a one-class SVM is trained from the features learned by the DBN. Since a linear kernel can be substituted for nonlinear ones in our hybrid model without loss of accuracy, our model is scalable and computationally efficient. The experimental results show that our proposed model yields comparable anomaly detection performance with a deep autoencoder, while reducing its training and testing time by a factor of 3 and 1000, respectively.