Teachers’ perceptions of the use of an external change agent in school curriculum change

An external change agent (ECA) was recently employed in three Queensland schools to align the school curriculum with the requirements of the state’s high stakes test known as the Queensland Core Skills test (QCS). This paper reports on the teachers’ perceptions of a change process led by an ECA. With the ever-increasing implementation of high stakes testing in Australian schools, teachers are under mounting pressure to produce ‘results’. Therefore, in order to maximise their students’ success in these tests, schools are altering their curricula to incorporate the test requirements. Rather than the traditional method of managing such curriculum change processes internally, there is a growing trend for principals to source external expertise in the form of ECAs. Although some academics, teachers, and much of the relevant literature, would regard such a practice as problematic, this study found that in fact, teachers were quite open to externally led curriculum change, especially if they perceived the leader to be knowledgeable and creditable in this area.

Using digital storytelling as a change agent for women’s participation in the Turkish public sphere

This thesis builds on the scholarship and practical know-how that have emerged from digital storytelling projects around the world with diverse groups of participants in a range of institutions. I have used the results of these projects to explore the opportunities Digital Storytelling workshop practice may hold for women’s participation in the public sphere in Turkey. Through theoretical discussion and practical experimentation, I examine the potential of Digital Storytelling workshop practice as a means to promote agency and self-expression in a feminist activist organisation, focusing in particular on whether Digital Storytelling can be used as a change agent – as a tool for challenging the idea of public sphere in ways that make it more inclusive of women’s participation. The thesis engages with feminist scholarship’s critiques of the public/private dichotomy, as well as the concept of gender, to seek connections with narrative identity in the light of the analysis of the Digital Storytelling workshops and the digital stories that were created in a feminist context. The study on which this thesis is based saw the introduction of Digital Storytelling to Turkey for the first time through workshops in Istanbul and Antakya, conducted in partnership with the feminist activist organisation Amargi Women’s Academy. Applying the principles of feminist post-structuralist discourse analysis as used by Judith Baxter (2003), I examine two sets of data collected in this project. First, I analyse the interactions during the Digital Storytelling workshops, where women from Amargi created their digital stories in a collaborative setting. This is done through participatory observation notes and in-depth interviews with the workshop participants and facilitators. Second, I seek to uncover the strategies that these women used to ‘speak back to power’ in their digital stories, reading these as texts. I conclude that women from the Amargi network used the workshops to create digital content in order to communicate their concerns about issues that can be classified as gender-specific matters. During this process, they also cooperated, established new connections, and at the end of the process even defined new ways of using, circulating and repurposing their digital stories for feminist activism in Turkey. My research thereby contributes equally to feminist discourse analysis, the study of new-media usage and uptake among non-professionals, and the study of media–public sphere interactions in a particular national setting: Turkey. My conclusion indicates that the process of production is as important as the product itself, and from that I am able to draw out some strategies for developing digitally equipped women’s activism in Turkey.

Modelling passenger flow at airport terminals : individual agent decision model for stochastic passenger behaviour

Airport system is complex. Passenger dynamics within it appear to be complicate as well. Passenger behaviours outside standard processes are regarded more significant in terms of public hazard and service rate issues. In this paper, we devised an individual agent decision model to simulate stochastic passenger behaviour in airport departure terminal. Bayesian networks are implemented into the decision making model to infer the probabilities that passengers choose to use any in-airport facilities. We aim to understand dynamics of the discretionary activities of passengers.

Roll the dice, rational agent : should extra-curial punishment mitigate an offender's sentence?

It was rugby league State of Origin night 2008 and a group of adults had descended upon a house in Eagleby, Brisbane to have some drinks and to celebrate the game. At 11pm that evening, Shane Thomas Davidson entered the bedroom of the homeowner’s 10-year-old son, TC. Davidson approached the bed and began to massage the boy’s penis under his clothing, which caused TC to wake. Davidson stated, ‘Show me how big your willy is and I’ll show you how big mine is’. TC refused the request and after a small period of time, left the bedroom and told his father what had happened...

Methodology to assess safety effects of future Intelligent Transport Systems on railway level crossings

There is consistent evidence showing that driver behaviour contributes to crashes and near miss incidents at railway level crossings (RLXs). The development of emerging Vehicle-to-Vehicle and Vehicle-to-Infrastructure technologies is a highly promising approach to improve RLX safety. To date, research has not evaluated comprehensively the potential effects of such technologies on driving behaviour at RLXs. This paper presents an on-going research programme assessing the impacts of such new technologies on human factors and drivers’ situational awareness at RLX. Additionally, requirements for the design of such promising technologies and ways to display safety information to drivers were systematically reviewed. Finally, a methodology which comprehensively assesses the effects of in-vehicle and road-based interventions warning the driver of incoming trains at RLXs is discussed, with a focus on both benefits and potential negative behavioural adaptations. The methodology is designed for implementation in a driving simulator and covers compliance, control of the vehicle, distraction, mental workload and drivers’ acceptance. This study has the potential to provide a broad understanding of the effects of deploying new in-vehicle and road-based technologies at RLXs and hence inform policy makers on safety improvements planning for RLX.

Tocotrienol as potential anticancer agent

Vitamin E is composed of two structurally similar compounds: tocopherols (TPs) and tocotrienols (T3). Despite being overshadowed by TP over the past few decades, T3 is now considered to be a promising anticancer agent due to its potent effects against a wide range of cancers. A growing body of evidence suggests that in addition to its antioxidative and pro-apoptotic functions, T3 possesses a number of anticancer properties that make it superior to TP. These include the inhibition of epithelial-to-mesenchymal transitions, the suppression of vascular endothelial growth factor tumor angiogenic pathway and the induction of antitumor immunity. More recently, T3, but not TP, has been shown to have chemosensitization and anti-cancer stem cell effects, further demonstrating the potential of T3 as an effective anticancer therapeutic agent. With most of the previous clinical studies on TP producing disappointing results, research has now focused on testing T3 as the next generation vitamin E for chemoprevention and cancer treatment. This review will summarize recent developments in the understanding of the anticancer effects of T3. We will also discuss current progress in clinical trials involving T3 as an adjuvant to conventional cancer therapy.

An intelligent network control system for plug-in electric vehicles and the associate communication mechanism

The development of an intelligent plug-in electric vehicle (PEV) network is an important research topic in the smart grid environment. An intelligent PEV network enables a flexible control of PEV charging and discharging activities and hence PEVs can be utilized as ancillary service providers in the power system concerned. Given this background, an intelligent PEV network architecture is first developed, and followed by detailed designs of its application layers, including the charging and discharging controlling system, mobility and roaming management, as well as communication mechanisms associated. The presented architecture leverages the philosophy in mobile communication network buildup

Response to “Topical agent therapy for prevention and treatment of radiodermatitis : a meta-analysis”

To the Editor; It was with interest that I read the recent article by Zhang et al. published in Supportive Care in Cancer [1]. This paper highlighted the importance of radiodermatitis (RD) being an unresolved and distressing clinical issue in patients with cancer undergoing radiation therapy. However, I am concerned with a number of clinical and methodological issues within this paper: (i) the clinical and operational definition of prophylaxis and treatment of RD; (ii) the accuracy of the identification of trials; and (iii) the appropriateness of the conduct of the meta-analyses...

Characterizing multi-agent team behavior from partial team tracings : evidence from the English Premier League

Real-world AI systems have been recently deployed which can automatically analyze the plan and tactics of tennis players. As the game-state is updated regularly at short intervals (i.e. point-level), a library of successful and unsuccessful plans of a player can be learnt over time. Given the relative strengths and weaknesses of a player’s plans, a set of proven plans or tactics from the library that characterize a player can be identified. For low-scoring, continuous team sports like soccer, such analysis for multi-agent teams does not exist as the game is not segmented into “discretized” plays (i.e. plans), making it difficult to obtain a library that characterizes a team’s behavior. Additionally, as player tracking data is costly and difficult to obtain, we only have partial team tracings in the form of ball actions which makes this problem even more difficult. In this paper, we propose a method to overcome these issues by representing team behavior via play-segments, which are spatio-temporal descriptions of ball movement over fixed windows of time. Using these representations we can characterize team behavior from entropy maps, which give a measure of predictability of team behaviors across the field. We show the efficacy and applicability of our method on the 2010-2011 English Premier League soccer data.

Feasibility of agent-based modelling of articular cartilage including a conceptual representation of its structure

Articular cartilage is a complex structure with an architecture in which fluid-swollen proteoglycans constrained within a 3D network of collagen fibrils. Because of the complexity of the cartilage structure, the relationship between its mechanical behaviours at the macroscale level and its components at the micro-scale level are not completely understood. The research objective in this thesis is to create a new model of articular cartilage that can be used to simulate and obtain insight into the micro-macro-interaction and mechanisms underlying its mechanical responses during physiological function. The new model of articular cartilage has two characteristics, namely: i) not use fibre-reinforced composite material idealization ii) Provide a framework for that it does probing the micro mechanism of the fluid-solid interaction underlying the deformation of articular cartilage using simple rules of repartition instead of constitutive / physical laws and intuitive curve-fitting. Even though there are various microstructural and mechanical behaviours that can be studied, the scope of this thesis is limited to osmotic pressure formation and distribution and their influence on cartilage fluid diffusion and percolation, which in turn governs the deformation of the compression-loaded tissue. The study can be divided into two stages. In the first stage, the distributions and concentrations of proteoglycans, collagen and water were investigated using histological protocols. Based on this, the structure of cartilage was conceptualised as microscopic osmotic units that consist of these constituents that were distributed according to histological results. These units were repeated three-dimensionally to form the structural model of articular cartilage. In the second stage, cellular automata were incorporated into the resulting matrix (lattice) to simulate the osmotic pressure of the fluid and the movement of water within and out of the matrix; following the osmotic pressure gradient in accordance with the chosen rule of repartition of the pressure. The outcome of this study is the new model of articular cartilage that can be used to simulate and study the micromechanical behaviours of cartilage under different conditions of health and loading. These behaviours are illuminated at the microscale level using the socalled neighbourhood rules developed in the thesis in accordance with the typical requirements of cellular automata modelling. Using these rules and relevant Boundary Conditions to simulate pressure distribution and related fluid motion produced significant results that provided the following insight into the relationships between osmotic pressure gradient and associated fluid micromovement, and the deformation of the matrix. For example, it could be concluded that: 1. It is possible to model articular cartilage with the agent-based model of cellular automata and the Margolus neighbourhood rule. 2. The concept of 3D inter connected osmotic units is a viable structural model for the extracellular matrix of articular cartilage. 3. Different rules of osmotic pressure advection lead to different patterns of deformation in the cartilage matrix, enabling an insight into how this micromechanism influences macromechanical deformation. 4. When features such as transition coefficient were changed, permeability (representing change) is altered due to the change in concentrations of collagen, proteoglycans (i.e. degenerative conditions), the deformation process is impacted. 5. The boundary conditions also influence the relationship between osmotic pressure gradient and fluid movement at the micro-scale level. The outcomes are important to cartilage research since we can use these to study the microscale damage in the cartilage matrix. From this, we are able to monitor related diseases and their progression leading to potential insight into drug-cartilage interaction for treatment. This innovative model is an incremental progress on attempts at creating further computational modelling approaches to cartilage research and other fluid-saturated tissues and material systems.

The Effects of Personality in a Social Context

The contextuality of changing attitudes makes them extremely difficult to model. This paper scales up Quantum Decision Theory (QDT) to a social setting, using it to model the manner in which social contexts can interact with the process of low elaboration attitude change. The elements of this extended theory are presented, along with a proof of concept computational implementation in a low dimensional subspace. This model suggests that a society's understanding of social issues will settle down into a static or frozen configuration unless that society consists of a range of individuals with varying personality types and norms.

Quantifying spatial structure in experimental observations and agent-based simulations using pair-correlation functions

We define a pair-correlation function that can be used to characterize spatiotemporal patterning in experimental images and snapshots from discrete simulations. Unlike previous pair-correlation functions, the pair-correlation functions developed here depend on the location and size of objects. The pair-correlation function can be used to indicate complete spatial randomness, aggregation or segregation over a range of length scales, and quantifies spatial structures such as the shape, size and distribution of clusters. Comparing pair-correlation data for various experimental and simulation images illustrates their potential use as a summary statistic for calibrating discrete models of various physical processes.