Synthesis of 4-arm star poly(L-Lactide) oligomers using an in situ-generated calcium-based initiator

Using an in situ-generated calcium-based initiating species derived from pentaerythritol, the bulk synthesis of well-defined 4-arm star poly(L-lactide) oligomers has been studied in detail. The substitution of the traditional initiator, stannous octoate with calcium hydride allowed the synthesis of oligomers that had both low PDIs and a comparable number of polymeric arms (3.7 – 3.9) to oligomers of similar molecular weight. Investigations into the degree of control observed during the course of the polymerization found that the insolubility of pentaerythritol in molten L-lactide resulted in an uncontrolled polymerization only when the feed mole ratio of L-lactide to pentaerythritol was 13. At feed ratios of 40 and greater, a pseudo-living polymerization was observed. As part of this study, in situ FT-Raman spectroscopy was demonstrated to be a suitable method to monitor the kinetics of the ring-opening polymerization (ROP) of lactide. The advantages of using this technique rather than FT-IR-ATR and 1H NMR for monitoring L-lactide consumption during polymerization are discussed.

Sampling perceptions; testing reality : an evidence-based approach to measurably improve information literacy and student research skills

Do commencing students possess the level of information literacy (IL) knowledge and skills they need to succeed at university? What impact does embedding IL within the engineering and design curriculum have? This paper reports on the self-perception versus the reality of IL knowledge and skills, across a large cohort of first year built environment and engineering students. Acting on the findings of this evaluation, the authors (a team of academic librarians) developed an intensive IL skills program which was integrated into a faculty wide unit. Perceptions, knowledge and skills were re-evaluated at the end of the semester to determine if embedded IL education made a difference. Findings reveal that both the perception and reality of IL skills were significantly and measurably improved.

Contracting for community development : a case study based perspective of a public sector client initiative in Hong Kong

The construction industry is known to be an important contributor towards the gross domestic product of many countries. Moreover, the health of the construction industry is positively correlated to the economic growth of a country and in many economies public sector clients account for a major share of construction works. Given this strength, it is important for public sector clients to initiate innovations aimed at the betterment of the industry. In this context, concern about sustainable development has been a major driver of some innovative initiatives in construction industries worldwide. Furthermore, the Government of Hong Kong regards both sustainability and community development as important criteria when planning and procuring construction projects. This paper is based on a case study of a public sector development project in Hong Kong, and presents the salient features of the procurement and contractual systems adopted in the project, which foster sustainability and community development. The reported interim findings are based on a preliminary document analysis that is part of an ongoing longitudinal case study into the project. The document analysis takes a three-pronged approach in terms of how the procurement and contractual systems foster economic, environmental and social sustainability, and sums up their impact on the community as a whole.

Event-related potential (ERP) correlates of impaired visuospatial memory in schizophrenia

Previous studies have reported that patients with schizophrenia demonstrate impaired performance during working memory (WM) tasks. The current study aimed to determine whether WM impairments in schizophrenia are accompanied by reduced slow wave (SW) activity during on-line maintenance of mnemonic information. Event-related potentials were obtained from patients with schizophrenia and well controls as they performed a visuospatial delayed response task. On 50% of trials, a distractor stimulus was introduced during the delay. Compared with controls, patients with schizophrenia produced less SW memory negativity, particularly over the right hemisphere, together with reduced frontal enhancement of SW memory negativity in response to distraction. The results indicate that patients with schizophrenia generate less maintenance phase neuronal activity during WM performance, especially under conditions of distraction.

Human brain regions required for the dividing and switching of attention between two features of a single object

This combined PET and ERP study was designed to identify the brain regions activated in switching and divided attention between different features of a single object using matched sensory stimuli and motor response. The ERP data have previously been reported in this journal [64]. We now present the corresponding PET data. We identified partially overlapping neural networks with paradigms requiring the switching or dividing of attention between the elements of complex visual stimuli. Regions of activation were found in the prefrontal and temporal cortices and cerebellum. Each task resulted in different prefrontal cortical regions of activation lending support to the functional subspecialisation of the prefrontal and temporal cortices being based on the cognitive operations required rather than the stimuli themselves.

Working memory correlates of three symptom clusters in schizophrenia

Examined whether discrete working memory deficits underlie positive, negative and disorganised symptoms of schizophrenia. 52 outpatients (mean age 37.5 yrs) with schizophrenia were studied using items drawn from the Positive and Negative Syndrome Scale (PANSS). Linear regression and correlational analyses were conducted to examine whether symptom dimension scores were related to performance on several tests of working memory function. Severity of negative symptoms correlated with reduced production of words during a verbal fluency task, impaired ability to hold letter and number sequences on-line and manipulate them simultaneously, reduced performance during a dual task, and compromised visuospatial working memory under distraction-free conditions. Severity of disorganisation symptoms correlated with impaired visuospatial working memory under conditions of distraction, failure of inhibition during a verbal fluency task, perseverative responding on a test of set-shifting ability, and impaired ability to judge the veracity of simple declarative statements. The present study provides evidence that the positive, negative and disorganised symptom dimensions of the PANSS constitute independent clusters, associated with unique patterns of working memory impairment.

Eye-movements and visual imagery : a working memory approach to the treatment of post-traumatic stress disorder

It has been claimed that the symptoms of post-traumatic stress disorder (PTSD) can be ameliorated by eye-movement desensitization-reprocessing therapy (EMD-R), a procedure that involves the individual making saccadic eye-movements while imagining the traumatic event. We hypothesized that these eye-movements reduce the vividness of distressing images by disrupting the function of the visuospatial sketchpad (VSSP) of working memory, and that by doing so they reduce the intensity of the emotion associated with the image. This hypothesis was tested by asking non-PTSD participants to form images of neutral and negative pictures under dual task conditions. Their images were less vivid with concurrent eye-movements and with a concurrent spatial tapping task that did not involve eye-movements. In the first three experiments, these secondary tasks did not consistently affect participants' emotional responses to the images. However, Expt 4 used personal recollections as stimuli for the imagery task, and demonstrated a significant reduction in emotional response under the same dual task conditions. These results suggest that, if EMD-R works, it does so by reducing the vividness and emotiveness of traumatic images via the VSSP of working memory. Other visuospatial tasks may also be of therapeutic value.

Prediction of adjacent vertebral fracture risk associated with vertebroplasty : a computer-based simulation study

Vertebrplasty involved injecting cement into a fractured vertebra to provide stabilisation. There is clinical evidence to suggest however that vertebroplasty may be assocated with a higher risk of adjacent vertebral fracture; which may be due to the change in material properties of the post-procedure vertebra modifying the transmission of mechanical stresses to adjacent vertebrae.

A Vision Based Target Detection System for Docking of an Autonomous Underwater Vehicle

This paper describes the development and preliminary experimental evaluation of a visionbased docking system to allow an Autonomous Underwater Vehicle (AUV) to identify and attach itself to a set of uniquely identifiable targets. These targets, docking poles, are detected using Haar rectangular features and rotation of integral images. A non-holonomic controller allows the Starbug AUV to orient itself with respect to the target whilst maintaining visual contact during the manoeuvre. Experimental results show the proposed vision system is capable of robustly identifying a pair of docking poles simultaneously in a variety of orientations and lighting conditions. Experiments in an outdoor pool show that this vision system enables the AUV to dock autonomously from a distance of up to 4m with relatively low visibility.

Effective employment-based training models for childcare workers

Childcare workers play a significant role in the learning and development of children in their care. This has major implications for the training of workers. Under new reforms of the childcare industry the Australian government now requires all workers to obtain qualifications from a vocational education and training provider (eg. Technical and Further Education) or university. Effective models of employment-based training are critical to provide training to highly competent workers. This paper presents findings from a study that examined current and emerging models of employment-based training in the childcare sector, particularly at the Diploma level. Semi-structured interviews were conducted with a sample of 16 participants who represented childcare directors, employers, and workers located in childcare services in urban, regional and remote locations in the State of Queensland. The study proposes a ‘best-fit’ employment-based training approach that is characterised by a compendium of five models instead of a ‘one size fits all’. Issues with successful implementation of the EBT models are also discussed

Evidence-based decision making to strengthen local governance : nutritional health interventions in Bantul and Gunungkidul

Since 2001, district governments have had the main responsibility for providing public health care in Indonesia. One of the main public health challenges facing many district governments is improving nutritional standards, particularly among poorer segments of the population. Developing effective policies and strategies for improving nutrition requires a multi-sectoral approach encompassing agricultural development policy, access to markets, food security (storage) programs, provision of public health facilities, and promotion of public awareness of nutritional health. This implies a strong need for a coordinated approach involving multiple government agencies at the district level. Due to diverse economic, agricultural, and infrastructure conditions across the country, district governments’ ought to be better placed than central government both to identify areas of greatest need for public nutrition interventions, and devise policies that reflect local characteristics. However, in the two districts observed in this study—Bantul and Gunungkidul—it was clear that local government capacity to generate, obtain and integrate evidence about local conditions into the policy-making process was still limited. In both districts, decision-makers tended to rely more on intuition,anecdote, and precedent in formulating policy. The potential for evidence-based decision making was also severely constrained by a lack of coordination and communication between agencies, and current arrangements related to central government fiscal transfers, which compel local governments to allocate funding to centrally determined programs and priorities.

Evidence based decision making to strenghten local governance : nutritional health interventions

Since 2001, district governments have had the main responsibility for providing public health care in Indonesia. One of the main public health challenges facing many district governments is improving nutritional standards, particularly among poorer segments of the population. Developing effective policies and strategies for improving nutrition requires a multi-sectoral approach encompassing agricultural development policy, access to markets, food security (storage) programs, provision of public health facilities, and promotion of public awareness of nutritional health. This implies a strong need for a coordinated approach involving multiple government agencies at the district level. Due to diverse economic, agricultural,and infrastructure conditions across the country, district governments’ ought to be better placed than central government both to identify areas of greatest need for public nutrition interventions, and devise policies that reflect local characteristics. However, in the two districts observed in this study—Bantul and Gunungkidul—it was clear that local government capacity to generate, obtain and integrate evidence about local conditions into the policy-making process was still limited. In both districts, decision-makers tended to rely more on intuition,anecdote, and precedent in formulating policy. The potential for evidence-based decision making was also severely constrained by a lack of coordination and communication between agencies, and current arrangements related to central government fiscal transfers, which compel local governments to allocate funding to centrally determined programs and priorities.

Robot navigation in sensor space

This thesis investigates the problem of robot navigation using only landmark bearings. The proposed system allows a robot to move to a ground target location specified by the sensor values observed at this ground target posi- tion. The control actions are computed based on the difference between the current landmark bearings and the target landmark bearings. No Cartesian coordinates with respect to the ground are computed by the control system. The robot navigates using solely information from the bearing sensor space. Most existing robot navigation systems require a ground frame (2D Cartesian coordinate system) in order to navigate from a ground point A to a ground point B. The commonly used sensors such as laser range scanner, sonar, infrared, and vision do not directly provide the 2D ground coordi- nates of the robot. The existing systems use the sensor measurements to localise the robot with respect to a map, a set of 2D coordinates of the objects of interest. It is more natural to navigate between the points in the sensor space corresponding to A and B without requiring the Cartesian map and the localisation process. Research on animals has revealed how insects are able to exploit very limited computational and memory resources to successfully navigate to a desired destination without computing Cartesian positions. For example, a honeybee balances the left and right optical flows to navigate in a nar- row corridor. Unlike many other ants, Cataglyphis bicolor does not secrete pheromone trails in order to find its way home but instead uses the sun as a compass to keep track of its home direction vector. The home vector can be inaccurate, so the ant also uses landmark recognition. More precisely, it takes snapshots and compass headings of some landmarks. To return home, the ant tries to line up the landmarks exactly as they were before it started wandering. This thesis introduces a navigation method based on reflex actions in sensor space. The sensor vector is made of the bearings of some landmarks, and the reflex action is a gradient descent with respect to the distance in sensor space between the current sensor vector and the target sensor vec- tor. Our theoretical analysis shows that except for some fully characterized pathological cases, any point is reachable from any other point by reflex action in the bearing sensor space provided the environment contains three landmarks and is free of obstacles. The trajectories of a robot using reflex navigation, like other image- based visual control strategies, do not correspond necessarily to the shortest paths on the ground, because the sensor error is minimized, not the moving distance on the ground. However, we show that the use of a sequence of waypoints in sensor space can address this problem. In order to identify relevant waypoints, we train a Self Organising Map (SOM) from a set of observations uniformly distributed with respect to the ground. This SOM provides a sense of location to the robot, and allows a form of path planning in sensor space. The navigation proposed system is analysed theoretically, and evaluated both in simulation and with experiments on a real robot.

Context-based chemistry : creating opportunities for fluid transitions between concepts and context

Nationally and internationally, context-based programs have been implemented in an attempt to engage students in chemistry through connecting the canonical science with the real-world. In Queensland, a context-based approach to chemistry was trialled in selected schools from 2002 but there is little research that investigates how students learn in a context-based setting. This paper presents one significant finding from an ethnographic study that explored the learning that occurred in an 11th grade context-based chemistry classroom in Queensland. The study found that by providing students with the opportunity to write, fluid transitions (or to-ing and fro-ing) between concepts and context were an outcome of context-based learning.

Rough set-based reasoning and pattern mining for information filtering

An information filtering (IF) system monitors an incoming document stream to find the documents that match the information needs specified by the user profiles. To learn to use the user profiles effectively is one of the most challenging tasks when developing an IF system. With the document selection criteria better defined based on the users’ needs, filtering large streams of information can be more efficient and effective. To learn the user profiles, term-based approaches have been widely used in the IF community because of their simplicity and directness. Term-based approaches are relatively well established. However, these approaches have problems when dealing with polysemy and synonymy, which often lead to an information overload problem. Recently, pattern-based approaches (or Pattern Taxonomy Models (PTM) [160]) have been proposed for IF by the data mining community. These approaches are better at capturing sematic information and have shown encouraging results for improving the effectiveness of the IF system. On the other hand, pattern discovery from large data streams is not computationally efficient. Also, these approaches had to deal with low frequency pattern issues. The measures used by the data mining technique (for example, “support” and “confidences”) to learn the profile have turned out to be not suitable for filtering. They can lead to a mismatch problem. This thesis uses the rough set-based reasoning (term-based) and pattern mining approach as a unified framework for information filtering to overcome the aforementioned problems. This system consists of two stages - topic filtering and pattern mining stages. The topic filtering stage is intended to minimize information overloading by filtering out the most likely irrelevant information based on the user profiles. A novel user-profiles learning method and a theoretical model of the threshold setting have been developed by using rough set decision theory. The second stage (pattern mining) aims at solving the problem of the information mismatch. This stage is precision-oriented. A new document-ranking function has been derived by exploiting the patterns in the pattern taxonomy. The most likely relevant documents were assigned higher scores by the ranking function. Because there is a relatively small amount of documents left after the first stage, the computational cost is markedly reduced; at the same time, pattern discoveries yield more accurate results. The overall performance of the system was improved significantly. The new two-stage information filtering model has been evaluated by extensive experiments. Tests were based on the well-known IR bench-marking processes, using the latest version of the Reuters dataset, namely, the Reuters Corpus Volume 1 (RCV1). The performance of the new two-stage model was compared with both the term-based and data mining-based IF models. The results demonstrate that the proposed information filtering system outperforms significantly the other IF systems, such as the traditional Rocchio IF model, the state-of-the-art term-based models, including the BM25, Support Vector Machines (SVM), and Pattern Taxonomy Model (PTM).