Multimodal imaging of the collagen and elastic fibre networks in the bovine intervertebral disc

INTRODUCTION. The intervertebral disc is the largest avascular structure in the human body, withstanding transient loads of up to nine times body weight during rigorous physical activity. The key structural elements of the disc are a gel-like nucleus pulposus surrounded by concentric lamellar rings containing criss-crossed collagen fibres. The disc also contains an elastic fiber network which has been suggested to play a structural role, but to date the relationship between the collagen and elastic fiber networks is unclear. CONCLUSION. The multimodal transmitted and reflected polarized light microscopy technique developed here allows clear differentiation between the collagen and elastic fiber networks of the intervertebral disc. The ability to image unstained specimens avoids concerns with uneven stain penetration or specificity of staining. In bovine tail discs, the elastic fiber network is intimately associated with the collagen network.

Posters versus lurkers: Improving participation in enterprise social networks through promotional messages

Enterprise social networks (ESNs) often fail if there are few or no contributors of content. Promotional messages are among the common interventions used to improve participation. While most users only read others’ content (i.e. lurk), contributors who create content (i.e. post) account for only 1% of the users. Research on interventions to improve participation across dissimilar groups is scarce especially in work settings. We develop a model that examines four key motivations of posting and lurking. We employ the elaboration likelihood model to understand how promotional messages influence lurkers’ and posters’ beliefs and participation. We test our model with data collected from 366 members in two corporate Google⁺ communities in a large Australian retail organization. We find that posters and lurkers are motivated and hindered by different factors. Promotional messages do not – always – yield the hoped-for results among lurkers; however, they do make posters more enthusiastic to participate.

Expectation and variation with a virtual die

By the time students reach the middle years they have experienced many chance activities based on dice. Common among these are rolling one die to explore the relationship of frequency and theoretical probability, and rolling two dice and summing the outcomes to consider their probabilities. Although dice may be considered overused by some, the advantage they offer is a familiar context within which to explore much more complex concepts. If the basic chance mechanism of the device is understood, it is possible to enter quickly into an arena of more complex concepts. This is what happened with a two hour activity engaged in by four classes of Grade 6 students in the same school. The activity targeted the concepts of variation and expectation. The teachers held extended discussions with their classes on variation and expectation at the beginning of the activity, with students contributing examples of the two concepts from their own experience. These notions are quite sophisticated for Grade 6, but the underlying concepts describe phenomena that students encounter every day. For example, time varies continuously; sporting results vary from game to game; the maximum temperature varies from day to day. However, there is an expectation about tomorrow’s maximum temperature based on the expert advice from the weather bureau. There may also be an expectation about a sporting result based on the participants’ previous results. It is this juxtaposition that makes life interesting. Variation hence describes the differences we see in phenomena around us. In a scenario displaying variation, expectation describes the effort to characterise or summarise the variation and perhaps make a prediction about the message arising from the scenario. The explicit purpose of the activity described here was to use the familiar scenario of rolling a die to expose these two concepts. Because the students had previously experienced rolling physical dice they knew instinctively about the variation that occurs across many rolls and about the theoretical expectation that each side should “come up” one-sixth of the time. They had observed the instances of the concepts in action, but had not consolidated the underlying terminology to describe it. As the two concepts are so fundamental to understanding statistics, we felt it would be useful to begin building in the familiar environment of rolling a die. Because hand-held dice limit the explorations students can undertake, the classes used the soft-ware TinkerPlots (Konold & Miller, 2011) to simulate rolling a die multiple times.

Cooperative diversity for performance enhancement of vehicular ad hoc networks

This project was a step forward in introducing suitable cooperative diversity transmission techniques for vehicle to vehicle communications. The contributions are intended to aid in the successful implementation of future vehicular safety and autonomous controlling systems. Several protocols were introduced for vehicles to communicate effectively without losing connectivity. This study investigated novel protocols in terms of diversity-multiplexing trade-off and outage for a range of potential vehicular safety and infotainment applications.

The role of tunnel junction resistances and defects on electron transport mechanism in networks of two-dimensional disordered conductors

The effect of tunnel junction resistances on the electronic property and the magneto-resistance of few-layer graphene sheet networks is investigated. By decreasing the tunnel junction resistances, transition from strong localization to weak localization occurs and magneto-resistance changes from positive to negative. It is shown that the positive magneto-resistance is due to Zeeman splitting of the electronic states at the Fermi level as it changes with the bias voltage. As the tunnel junction resistances decrease, the network resistance is well described by 2D weak localization model. Sensitivity of the magneto-resistance to the bias voltage becomes negligible and diminishes with increasing temperature. It is shown 2D weak localization effect mainly occurs inside of the few-layer graphene sheets and the minimum temperature of 5 K in our experiments is not sufficiently low to allow us to observe 2D weak localization effect of the networks as it occurs in 2D disordered metal films. Furthermore, defects inside the few-layer graphene sheets have negligible effect on the resistance of the networks which have small tunnel junction resistances between few-layer graphene sheets

Fractal and multifractal properties of a family of fractal networks

In this work, we study the fractal and multifractal properties of a family of fractal networks introduced by Gallos et al (2007 Proc. Nat. Acad. Sci. USA 104 7746). In this fractal network model, there is a parameter e which is between 0 and 1, and allows for tuning the level of fractality in the network. Here we examine the multifractal behavior of these networks, the dependence relationship of the fractal dimension and the multifractal parameters on parameter e. First, we find that the empirical fractal dimensions of these networks obtained by our program coincide with the theoretical formula given by Song et al (2006 Nature Phys. 2 275). Then from the shape of the τ(q) and D(q) curves, we find the existence of multifractality in these networks. Last, we find that there exists a linear relationship between the average information dimension 〈D(1)〉 and the parameter e.

A quantitative metric to identify critical elements within seafood supply networks

A theoretical basis is required for comparing key features and critical elements in wild fisheries and aquaculture supply chains under a changing climate. Here we develop a new quantitative metric that is analogous to indices used to analyse food-webs and identify key species. The Supply Chain Index (SCI) identifies critical elements as those elements with large throughput rates, as well as greater connectivity. The sum of the scores for a supply chain provides a single metric that roughly captures both the resilience and connectedness of a supply chain. Standardised scores can facilitate cross-comparisons both under current conditions as well as under a changing climate. Identification of key elements along the supply chain may assist in informing adaptation strategies to reduce anticipated future risks posed by climate change. The SCI also provides information on the relative stability of different supply chains based on whether there is a fairly even spread in the individual scores of the top few key elements, compared with a more critical dependence on a few key individual supply chain elements. We use as a case study the Australian southern rock lobster Jasus edwardsii fishery, which is challenged by a number of climate change drivers such as impacts on recruitment and growth due to changes in large-scale and local oceanographic features. The SCI identifies airports, processors and Chinese consumers as the key elements in the lobster supply chain that merit attention to enhance stability and potentially enable growth. We also apply the index to an additional four real-world Australian commercial fishery and two aquaculture industry supply chains to highlight the utility of a systematic method for describing supply chains. Overall, our simple methodological approach to empirically-based supply chain research provides an objective method for comparing the resilience of supply chains and highlighting components that may be critical.

A CCG virtual system for big data application communication costs analysis

Network topology and routing are two important factors in determining the communication costs of big data applications at large scale. As for a given Cluster, Cloud, or Grid system, the network topology is fixed and static or dynamic routing protocols are preinstalled to direct the network traffic. Users cannot change them once the system is deployed. Hence, it is hard for application developers to identify the optimal network topology and routing algorithm for their applications with distinct communication patterns. In this study, we design a CCG virtual system (CCGVS), which first uses container-based virtualization to allow users to create a farm of lightweight virtual machines on a single host. Then, it uses software-defined networking (SDN) technique to control the network traffic among these virtual machines. Users can change the network topology and control the network traffic programmingly, thereby enabling application developers to evaluate their applications on the same system with different network topologies and routing algorithms. The preliminary experimental results through both synthetic big data programs and NPB benchmarks have shown that CCGVS can represent application performance variations caused by network topology and routing algorithm.

Potential uses of Bayesian networks as tools for synthesis of systematic reviews of complex interventions

Bayesian networks (BNs) are tools for representing expert knowledge or evidence. They are especially useful for synthesising evidence or belief concerning a complex intervention, assessing the sensitivity of outcomes to different situations or contextual frameworks and framing decision problems that involve alternative types of intervention. Bayesian networks are useful extensions to logic maps when initiating a review or to facilitate synthesis and bridge the gap between evidence acquisition and decision-making. Formal elicitation techniques allow development of BNs on the basis of expert opinion. Such applications are useful alternatives to ‘empty’ reviews, which identify knowledge gaps but fail to support decision-making. Where review evidence exists, it can inform the development of a BN. We illustrate the construction of a BN using a motivating example that demonstrates how BNs can ensure coherence, transparently structure the problem addressed by a complex intervention and assess sensitivity to context, all of which are critical components of robust reviews of complex interventions. We suggest that BNs should be utilised to routinely synthesise reviews of complex interventions or empty reviews where decisions must be made despite poor evidence.

Collaborative learning from distributed places and spaces: Exploring the use of virtual collaborative tools for local and global student teamwork projects

Educating responsive graduates. Graduate competencies include reliability, communication skills and ability to work in teams. Students using Collaborative technologies adapt to a new working environment, working in teams and using collaborative technologies for learning. Collaborative Technologies were used not simply for delivery of learning but innovatively to supplement and enrich research-based learning, providing a space for active engagement and interaction with resources and team. This promotes the development of responsive ‘intellectual producers’, able to effectively communicate, collaborate and negotiate in complex work environments. Exploiting technologies. Students use ‘new’ technologies to work collaboratively, allowing them to experience the reality of distributed workplaces incorporating both flexibility and ‘real’ time responsiveness. Students are responsible and accountable for individual and group work contributions in a highly transparent and readily accessible workspace. This experience provides a model of an effective learning tool. Navigating uncertainty and complexity. Collaborative technologies allows students to develop critical thinking and reflective skills as they develop a group product. In this forum students build resilience by taking ownership and managing group work, and navigating the uncertainties and complexities of group dynamics as they constructively and professionally engage in team dialogue and learn to focus on the goal of the team task.

Designing informal learning experiences for early career academics using a knowledge ecosystem model

This article presents a ‘knowledge ecosystem’ model of how early career academics experience using information to learn while building their social networks for developmental purposes. Developed using grounded theory methodology, the model offers a way of conceptualising how to empower early career academics through 1) agency (individual and relational) and 2) facilitation of personalised informal learning (design of physical and virtual systems and environments) in spaces where developmental relationships are formed including programs, courses, events, community, home and social media. It is suggested that the knowledge ecosystem model is suitable for use in designing informal learning experiences for early career academics.

Application of power electronics in improving power quality and supply efficiency of AC traction networks

Major advances in power electronics during recent years have prompted considerable interest within the traction community. The capability of new technologies to reduce the AC railway networks' effect on power quality and improve their supply efficiency is expected to significantly decrease the cost of electric rail supply systems. Of particular interest are Static Frequency Converter (SFC), Rail Power Conditioner (RPC), High Voltage Direct Current (HVDC) and Energy Storage Systems (ESS) solutions. Substantial impacts on future feasibility of railway electrification are anticipated. Aurizon, Australia's largest heavy haul railway operator, has recently commissioned the world's first 50Hz/50Hz SFC installation and is currently investigating SFC, RPC, HVDC and ESS solutions. This paper presents a summary of current and emerging technologies with a particular focus on the potential techno-economic benefits.

Leveraging coherent distributed space-time codes for noncoherent communication in relay networks via training

For point to point multiple input multiple output systems, Dayal-Brehler-Varanasi have proved that training codes achieve the same diversity order as that of the underlying coherent space time block code (STBC) if a simple minimum mean squared error estimate of the channel formed using the training part is employed for coherent detection of the underlying STBC. In this letter, a similar strategy involving a combination of training, channel estimation and detection in conjunction with existing coherent distributed STBCs is proposed for noncoherent communication in Amplify-and-Forward (AF) relay networks. Simulation results show that the proposed simple strategy outperforms distributed differential space-time coding for AF relay networks. Finally, the proposed strategy is extended to asynchronous relay networks using orthogonal frequency division multiplexing.

Covalently bonded networks through surface-confined polymerization

The prospect of synthesizing ordered, covalently bonded structures directly on a surface has recently attracted considerable attention due to its fundamental interest and for potential applications in electronics and photonics. This prospective article focuses on efforts to synthesize and characterize epitaxial one- and two-dimensional (1D and 2D, respectively) polymeric networks on single crystal surfaces. Recent studies, mostly performed using scanning tunneling microscopy (STM), demonstrate the ability to induce polymerization based on Ullmann coupling, thermal dehalogenation and dehydration reactions. The 2D polymer networks synthesized to date have exhibited structural limitations and have been shown to form only small domains on the surface. We discuss different approaches to control 1D and 2D polymerization, with particular emphasis on the surface phenomena that are critical to the formation of larger ordered domains.

Compositional agent-based models for electricity distribution networks

This thesis presents a novel approach to building large-scale agent-based models of networked physical systems using a compositional approach to provide extensibility and flexibility in building the models and simulations. A software framework (MODAM - MODular Agent-based Model) was implemented for this purpose, and validated through simulations. These simulations allow assessment of the impact of technological change on the electricity distribution network looking at the trajectories of electricity consumption at key locations over many years.