In vitro and in vivo analysis of co-electrospun scaffolds made of medical grade poly(epsilon-caprolactone) and porcine collagen

In this study, a nanofiber mesh made by co-electrospinning medical grade poly(epsilon-caprolactone) and collagen (mPCL/Col) was fabricated and studied. Its mechanical properties and characteristics were analyzed and compared to mPCL meshes. mPCL/Col meshes showed a reduction in strength but an increase in ductility when compared to PCL meshes. In vitro assays revealed that mPCL/Col supported the attachment and proliferation of smooth muscle cells on both sides of the mesh. In vivo studies in the corpus cavernosa of rabbits revealed that the mPCL/Col scaffold used in conjunction with autologous smooth muscle cells resulted in better integration with host tissue when compared to cell free scaffolds. On a cellular level preseeded scaffolds showed a minimized foreign body reaction.

Young children's early modelling with data

An educational priority of many nations is to enhance mathematical learning in early childhood. One area in need of special attention is that of statistics. This paper argues for a renewed focus on statistical reasoning in the beginning school years, with opportunities for children to engage in data modelling activities. Such modelling involves investigations of meaningful phenomena, deciding what is worthy of attention (i.e., identifying complex attributes), and then progressing to organising, structuring, visualising, and representing data. Results are reported from the first year of a three-year longitudinal study in which three classes of first-grade children and their teachers engaged in activities that required the creation of data models. The theme of “Looking after our Environment,” a component of the children’s science curriculum at the time, provided the context for the activities. Findings focus on how the children dealt with given complex attributes and how they generated their own attributes in classifying broad data sets, and the nature of the models the children created in organising, structuring, and representing their data.

Interdisciplinary modelling

This article examines one approach to promoting creative and flexible use of mathematical ideas within an interdisciplinary context in the primary curriculum, namely, through modelling. Three classes of fifth-grade children worked on a modelling problem, The First Fleet (Australia’s settlement), situated within the curriculum domains of science and studies of society and environment. Reported here are the cycles of development displayed by one group of children as they worked the problem, together with the range of models created across the classes. Children developed mathematisation processes that extended beyond their regular curriculum, including identifying and prioritising key problem elements, exploring relationships among elements, quantifying qualitative data, ranking and aggregating data, and creating and working with weighted scores. Aspects of Goldin’s (2000, 2007) affective structures also appeared to play an important role in the children's mathematical developments.

Using concept mapping to scaffold learning for students who experience learning difficulties in science classes

In order to develop scientific literacy students need the cognitive tools that enable them to read and evaluate science texts. One cognitive tool that has been widely used in science education to aid the development of conceptual understanding is concept mapping. However, it has been found some students experience difficulty with concept map construction. This study reports on the development and evaluation of an instructional sequence that was used to scaffold the concept-mapping process when middle school students who were experiencing difficulty with science learning used concept mapping to summarise a chapter of a science text. In this study individual differences in working memory functioning are suggested as one reason that students experience difficulty with concept map construction. The study was conducted using a design-based research methodology in the school’s learning support centre. The analysis of student work samples collected during the two-year study identified some of the difficulties and benefits associated with the use of scaffolded concept mapping with these students. The observations made during this study highlight the difficulty that some students experience with the use of concept mapping as a means of developing an understanding of science concepts and the amount of instructional support that is required for such understanding to develop. Specifically, the findings of the study support the use of multi-component, multi-modal instructional techniques to facilitate the development of conceptual understanding with students who experience difficulty with science learning. In addition, the important roles of interactive dialogue and metacognition in the development of conceptual understanding are identified.

Engaging students in large classes using Elluminate

The advancement of online teaching environments during the past several years presents an exciting opportunity to extend existing teaching methodologies. The software package known as Elluminate is one example of a virtual classroom, facilitating the provision of real time interaction, collaboration and group meetings. This paper will examine the use of Elluminate in the teaching of large classes. The use of such technology for large classes is of particular interest, as large classes are often, unfairly, associated with a reputation for being impersonal as well as notions of conveyor belt learning. In this paper the potential to extend teaching and learning opportunities using Elluminate, in the context of large classes, will be explored. It will be shown that the use of technology such as Elluminate can assist in providing students with a more flexible means of accessing academic support, as well as allowing for a customised delivery of course content so as to focus learning outcomes.

Motor conflict in Stroop tasks : direct evidence from single-trial electro-myography and electro-encephalography

Several brain imaging studies have assumed that response conflict is present in Stroop tasks. However, this has not been demonstrated directly. We examined the time-course of stimulus and response conflict resolution in a numerical Stroop task by combining single-trial electro-myography (EMG) and event-related brain potentials (ERP). EMG enabled the direct tracking of response conflict and the peak latency of the P300 ERP wave was used to index stimulus conflict. In correctly responded trials of the incongruent condition EMG detected robust incorrect response hand activation which appeared consistently in single trials. In 50–80% of the trials correct and incorrect response hand activation coincided temporally, while in 20–50% of the trials incorrect hand activation preceded correct hand activation. EMG data provides robust direct evidence for response conflict. However, congruency effects also appeared in the peak latency of the P300 wave which suggests that stimulus conflict also played a role in the Stroop paradigm. Findings are explained by the continuous flow model of information processing: Partially processed task-irrelevant stimulus information can result in stimulus conflict and can prepare incorrect response activity. A robust congruency effect appeared in the amplitude of incongruent vs. congruent ERPs between 330–400 ms, this effect may be related to the activity of the anterior cingulate cortex.

The power of a single prototype : sustainable fashion textile design and the prevention of carcinogenic melanoma

Is there a role for prototyping (sketching, pattern making and sampling) in addressing real world problems of sustainability (People, Profit, and Planet), in this case social/healthcare issues, through fashion and textiles research? Skin cancer and related illnesses are a major cause of disfigurement and death in New Zealand and Australia where the rates of Melanoma, a serious form of skin cancer, are four times higher than in the Northern Hemisphere regions of USA, UK and Canada (IARC, 1992). In 2007, AUT University (Auckland University of Technology) Fashion Department and the Health Promotion Department of Cancer Society - Auckland Division (CSA) developed a prototype hat aimed at exploring a barrier type solution to prevent facial and neck skin damage. This is a paradigm shift from the usual medical research model. This paper provides an overview of the project and examines how a fashion prototype has been used to communicate emergent social, environmental, personal, physiological and technological concerns to the trans-disciplinary research team. The authors consider how the design of a product can enhance and support sustainable design practice while contributing a potential solution to an ongoing health issue. Analysis of this case study provides an insight into prototyping in fashion and textiles design, user engagement and the importance of requirements analysis in relation to sustainable development. The analysis and a successful outcome of the final prototype have provided a gateway to future collaborative research and product development.

Mapping a suburb with a single camera using a biologically inspired SLAM system

This paper describes a biologically inspired approach to vision-only simultaneous localization and mapping (SLAM) on ground-based platforms. The core SLAM system, dubbed RatSLAM, is based on computational models of the rodent hippocampus, and is coupled with a lightweight vision system that provides odometry and appearance information. RatSLAM builds a map in an online manner, driving loop closure and relocalization through sequences of familiar visual scenes. Visual ambiguity is managed by maintaining multiple competing vehicle pose estimates, while cumulative errors in odometry are corrected after loop closure by a map correction algorithm. We demonstrate the mapping performance of the system on a 66 km car journey through a complex suburban road network. Using only a web camera operating at 10 Hz, RatSLAM generates a coherent map of the entire environment at real-time speed, correctly closing more than 51 loops of up to 5 km in length.

Single camera vision-only SLAM on a suburban road network

Simultaneous Localization And Mapping (SLAM) is one of the major challenges in mobile robotics. Probabilistic techniques using high-end range finding devices are well established in the field, but recent work has investigated vision only approaches. This paper presents a method for generating approximate rotational and translation velocity information from a single vehicle-mounted consumer camera, without the computationally expensive process of tracking landmarks. The method is tested by employing it to provide the odometric and visual information for the RatSLAM system while mapping a complex suburban road network. RatSLAM generates a coherent map of the environment during an 18 km long trip through suburban traffic at speeds of up to 60 km/hr. This result demonstrates the potential of ground based vision-only SLAM using low cost sensing and computational hardware.

Single-layer decoupling networks for large circulant symmetric arrays

In this paper, the authors propose a new structure for the decoupling of circulant symmetric arrays of more than four elements. In this case, network element values are again obtained through a process of repeated eigenmode decoupling, here by solving sets of nonlinear equations. However, the resulting circuit is much simpler and can be implemented on a single layer. The corresponding circuit topology for the 6-element array is displayed in figure diagrams. The procedure will be illustrated by considering different examples.

Single case experimental design : an overview

Background: In health related research, it is critical not only to demonstrate the efficacy of intervention, but to show that this is not due to chance or confounding variables. Content: Single case experimental design is a useful quasi-experimental design and method used to achieve these goals when there are limited participants and funds for research. This type of design has various advantages compared to group experimental designs. One such advantage is the capacity to focus on individual performance outcomes compared to group performance outcomes. Conclusions: This comprehensive review demonstrates the benefits and limitations of using single case experimental design, its various design methods, and data collection and analysis for research purposes.

Bayesian models for longitudinal data

Longitudinal data, where data are repeatedly observed or measured on a temporal basis of time or age provides the foundation of the analysis of processes which evolve over time, and these can be referred to as growth or trajectory models. One of the traditional ways of looking at growth models is to employ either linear or polynomial functional forms to model trajectory shape, and account for variation around an overall mean trend with the inclusion of random eects or individual variation on the functional shape parameters. The identification of distinct subgroups or sub-classes (latent classes) within these trajectory models which are not based on some pre-existing individual classification provides an important methodology with substantive implications. The identification of subgroups or classes has a wide application in the medical arena where responder/non-responder identification based on distinctly diering trajectories delivers further information for clinical processes. This thesis develops Bayesian statistical models and techniques for the identification of subgroups in the analysis of longitudinal data where the number of time intervals is limited. These models are then applied to a single case study which investigates the neuropsychological cognition for early stage breast cancer patients undergoing adjuvant chemotherapy treatment from the Cognition in Breast Cancer Study undertaken by the Wesley Research Institute of Brisbane, Queensland. Alternative formulations to the linear or polynomial approach are taken which use piecewise linear models with a single turning point, change-point or knot at a known time point and latent basis models for the non-linear trajectories found for the verbal memory domain of cognitive function before and after chemotherapy treatment. Hierarchical Bayesian random eects models are used as a starting point for the latent class modelling process and are extended with the incorporation of covariates in the trajectory profiles and as predictors of class membership. The Bayesian latent basis models enable the degree of recovery post-chemotherapy to be estimated for short and long-term followup occasions, and the distinct class trajectories assist in the identification of breast cancer patients who maybe at risk of long-term verbal memory impairment.