Isolation of two phenylethanoid glycosides from Eremophila gilesii

The leaves of Eremophila gilesii have been used traditionally to treat colds, headaches, sores, and chest pains. Our previous screening of Australian native plants showed that the methanol extract of the aerial parts of E. gilesii demonstrated notable inhibition of ADP-induced human platelet aggregation and serotonin release. Subsequent fractionation on the methanol extract led to the isolation of two phenylethanoid glycosides, verbascoside (1) and poliumoside (2). This is the first study reporting the presence of phenylethanoid glycosides in E. gilesii.

Chromosome 17 and the inducible nitric oxide synthase gene in human essential hypertension

Essential hypertension is a common multifactorial trait that results in a significantly increased risk for heart attack and stroke. The condition has a genetic basis, although at present the number of genes is unknown. In order to identify such genes, we are utilising a linkage scanning approach using microsatellite markers and affected sibships. Here we provide evidence for the location of at least one hypertension susceptibility locus on chromosome 17. Analysis of 177 affected sibpairs gave evidence for significant excess allele sharing to D17S949 (SPLINK: P=0.0029; MAPMAKER SIBS: P=0.0033; ASPEX: P=0.0061; GENEHUNTER: P=0.0096; ANALYZE (SIBPAIR): P=0.0025) on 17q22–24, with significant allele sharing also indicated for an additional marker, D17S799 (SPLINK: P=0.025; MAPMAKER SIBS: P= 0.025) located close to the centromere. Since these two genomic regions are well separated, our results indicate that there may be more than one chromosome 17 locus affecting human blood pressure. Moreover, further investigation of this chromosome, utilizing a polymorphism within the promoter of the iNOS candidate gene, NOS2A, revealed both increased allele sharing among sibpairs (SPLINK: P=0.02; ASPEX: P=0.00004) and positive association (P= 0.034) of NOS2A to essential hypertension. Hence these results indicate that chromosome 17 and, more specifically, the NOS2A gene may play a role in human essential hypertension.

Preparing for performance capture #1

This video article articulates two exercises that have been developed to respond to the need for preparedness in the growing field of Performance Capture. The first is called Walking Through (Delbridge 2013), where the actor navigates a series of objects that exist in screen space through a developed sense of the existing physical particularities of the studio and an interaction with a screen (or feedback loop). The second exercise is called The Donut (Delbridge 2013), where the performer continues to navigate screen space but this time does so through the literal stepping through of a Torus in the virtual – again with nothing but the studio infrastructure and the screen as a guide. Notions of Motion Captured performance infer the existence of an interface that combines performer with system, separating (or intervening in) the space between performance and the screen. It is precisely the effect and provided opportunity of the intermediary device on the practice, craft and preparedness of the actor as they navigate the connection between 3D screen space and the physical properties of the studio that is examined here. Defining the scope of current practice for the contemporary actor is a key construct of this challenge, with the most appropriate definition revolving around the provision of a required mixture of performance and content for live, mediated, framed and variously captured formats. One of these particular formats is Performance Capture. The exercises presented here are two from a series, developed over a three year study that contribute to our understanding of the potential for a training regimen to be developed for the rigors of Performance Capture.

Robots for environmental monitoring : significant advancements and applications

Robotic systems are increasingly being utilised as fundamental data-gathering tools by scientists, allowing new perspectives and a greater understanding of the planet and its environmental processes. Today's robots are already exploring our deep oceans, tracking harmful algal blooms and pollution spread, monitoring climate variables, and even studying remote volcanoes. This article collates and discusses the significant advancements and applications of marine, terrestrial, and airborne robotic systems developed for environmental monitoring during the last two decades. Emerging research trends for achieving large-scale environmental monitoring are also reviewed, including cooperative robotic teams, robot and wireless sensor network (WSN) interaction, adaptive sampling and model-aided path planning. These trends offer efficient and precise measurement of environmental processes at unprecedented scales that will push the frontiers of robotic and natural sciences.

Making the train : re-conceptualising accessibility for intra-urban rail travel

Australian authorities have set ambitious policy objectives to shift Australia’s current transport profile of heavy reliance on private motor cars to sustainable modes. Improving accessibility of public transport is a central component of that objective. Past studies on accessibility to public transport focus on walking time and/or waiting time. However, travellers’ perceptions of the interface leg journeys may depend not only on these direct and tangible factors but also on social and psychological factors. This paper extends previous research that identified five salient perspectives of rail access by means of a statement sorting activity and cluster analysis with a small sample of rail passengers in three Australian cities (Zuniga et al, 2013). This study collects a new data set including 144 responses from Brisbane and Melbourne to an online survey made up of a Likert-scaled statement sorting exercise and questionnaire. It employs factor analysis to examine the statement rankings and uncovers seven underlying factors in the exploratory manner, i.e., station, safety, access, transfer, service attitude, traveler’s physical activity levels, and environmental concern. Respondents from groups stratified by rail use frequency are compared in terms of their scores of those factors. Findings from this study indicate a need to re-conceptualize accessibility to intra-urban rail travel in agreement with current policy agenda, and to target behavioral intervention to multiple dimensions of accessibility influencing passengers’ travel choices. Arguments in this paper are not limited to intra-urban rail transit, but may also be relevant to public transport in general.

Making the train : re-conceptualising accessibility for intra-urban rail travel

Australian authorities have set ambitious policy objectives to shift Australia’s current transport profile of heavy reliance on private motor cars to sustainable modes. Improving accessibility of public transport is a central component of that objective. Past studies on accessibility to public transport focus on walking time and/or waiting time. However, travellers’ perceptions of the interface leg journeys may depend not only on these direct and tangible factors but also on social and psychological factors. This paper extends previous research that identified five salient perspectives of rail access by means of a statement sorting activity and cluster analysis with a small sample of rail passengers in three Australian cities (Zuniga et al, 2013). This study collects a new data set including 144 responses from Brisbane and Melbourne to an online survey made up of a Likert-scaled statement sorting exercise and questionnaire. It employs factor analysis to examine the statement rankings and uncovers seven underlying factors in the exploratory manner, i.e., station, safety, access, transfer, service attitude, traveler’s physical activity levels, and environmental concern. Respondents from groups stratified by rail use frequency are compared in terms of their scores of those factors. Findings from this study indicate a need to re-conceptualize accessibility to intra-urban rail travel in agreement with current policy agenda, and to target behavioral intervention to multiple dimensions of accessibility influencing passengers’ travel choices. Arguments in this paper are not limited to intra-urban rail transit, but may also be relevant to public transport in general.

An investigation of the 5-HT2C receptor gene as a migraine candidate gene

Migraine is a common complex disorder, currently classified into two main subtypes, migraine with aura (MA) and migraine without aura (MO). The strong preponderance of females to males suggests an X-linked genetic component. Recent studies have identified an X chromosomal susceptibility region (Xq24-q28) in two typical migraine pedigrees. This region harbours a potential candidate gene for the disorder, the serotonin receptor 2C (5-HT2C) gene. This study involved a linkage and association approach to investigate two single nucleotide variants in the 5-HT2C gene. In addition, exonic coding regions of the 5-HT2C gene were also sequenced for mutations in X-linked migraine pedigrees. Results of this study did not detect any linkage or association, and no disease causing mutations were identified. Hence, results for this study do not support a significant role of the 5-HT 2C gene in migraine predisposition. © 2003 Wiley-Liss, Inc.

Pre-crash and non-crash traffic flow trends analysis on motorways

Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence, reducing the frequency of crashes assists in addressing congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a short time window around the time of a crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists. We will compare them with normal traffic trends and show this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding to traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash. Using the K-Means clustering method with Euclidean distance function allowed the crashes to be clustered. Then, normal situation data was extracted based on the time distribution of crashes and were clustered to compare with the “high risk” clusters. Five major trends have been found in the clustering results for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Based on these findings, crash likelihood estimation models can be fine-tuned based on the monitored traffic conditions with a sliding window of 30 minutes to increase accuracy of the results and minimize false alarms.

Does a functional activity programme improve function, quality of life, and falls for residents in long term care? Cluster randomised controlled trial

Objective To assess the effectiveness of an activity programme in improving function, quality of life, and falls in older people in residential care. Design Cluster randomised controlled trial with one year follow-up. Setting 41low level dependency residential carehomes in New Zealand. Participants 682 people aged 65 years or over. Interventions 330 residents were offered a goal setting and individualised activities of daily living activity programme by a gerontology nurse, reinforced by usual healthcare assistants; 352 residents received social visits. Main outcome measures Function (late life function and disability instruments, elderly mobility scale, FICSIT-4

Promoting independence in residential care : successful recruitment for a randomised controlled trial

OBJECTIVES: To describe the recruitment strategy and association between facility and staff characteristics and success of resident recruitment for the Promoting Independence in Residential Care (PIRC) trial. DESIGN: Cross-sectional study of staff and facility characteristics and recruitment rates within facilities with calculation of cluster effects of multiple measures. SETTING AND PARTICIPANTS: Staff of low-level dependency residential care facilities and residents able to engage in a physical activity program in 2 cities in New Zealand. MEASURES: A global impression of staff willingness to facilitate research was gauged by research nurses, facility characteristics were measured by staff interview. Relevant outcomes were measured by resident interview and included the following: (1) Function: Late Life FDI scale, timed-up-and-go, FICSIT balance scale and the Elderly Mobility Scale; (2) Quality of Life: EuroQol quality of life scale, Life Satisfaction Index; and (3) falls were assessed by audit of the medical record. Correlation between recruitment rates, facility characteristics and global impression of staff willingness to participate were investigated. Design effects were calculated on outcomes. RESULTS: Forty-one (85%) facilities and 682 (83%) residents participated, median age was 85 years (range 65-101), and 74% were women. Participants had complex health problems. Recruitment rates were associated (but did not increase linearly) with the perceived willingness of staff, and were not associated with facility size. Design effects from the cluster recruitment differed according to outcome. CONCLUSIONS: The recruitment strategy was successful in recruiting a large sample of people with complex comorbidities and high levels of functional disability despite perceptions of staff reluctance. Staff willingness was related to recruitment success.

Distinguishing between mean-field, moment dynamics and stochastic descriptions of birth-death-movement processes

Mathematical descriptions of birth–death–movement processes are often calibrated to measurements from cell biology experiments to quantify tissue growth rates. Here we describe and analyze a discrete model of a birth–death-movement process applied to a typical two–dimensional cell biology experiment. We present three different descriptions of the system: (i) a standard mean–field description which neglects correlation effects and clustering; (ii) a moment dynamics description which approximately incorporates correlation and clustering effects, and; (iii) averaged data from repeated discrete simulations which directly incorporates correlation and clustering effects. Comparing these three descriptions indicates that the mean–field and moment dynamics approaches are valid only for certain parameter regimes, and that both these descriptions fail to make accurate predictions of the system for sufficiently fast birth and death rates where the effects of spatial correlations and clustering are sufficiently strong. Without any method to distinguish between the parameter regimes where these three descriptions are valid, it is possible that either the mean–field or moment dynamics model could be calibrated to experimental data under inappropriate conditions, leading to errors in parameter estimation. In this work we demonstrate that a simple measurement of agent clustering and correlation, based on coordination number data, provides an indirect measure of agent correlation and clustering effects, and can therefore be used to make a distinction between the validity of the different descriptions of the birth–death–movement process.

Segmentation of cone-beam CT using a hidden Markov random field with informative priors

Cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. The rich sources of prior information in IGRT are incorporated into a hidden Markov random field model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk. The voxel labels are estimated using iterated conditional modes. The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom. The mean voxel-wise misclassification rate was 6.2\%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

Hydrothermally formed functional niobium oxide doped tungsten nanorods

Nanorod forms of metal oxides is recognised as one of the most remarkable morphologies. Their structure and functionality have driven important advancements in a vast range of electronic devices and applications. In this work, we postulate a novel concept to explain how numerous localised surface states can be engineered into the bandgap of niobium oxide nanorods using tungsten. We discuss their contributions as local state surface charges for the modulation of a Schottky barrier height, relative dielectric constant and their respective conduction mechanisms. Their effect on the hydrogen gas molecule interactions mechanisms are also examined herein. We synthesised niobium tungsten oxide (Nb17W2O25) nanorods via a hydrothermal growth method and evaluated the Schottky barrier height, ideality factor, dielectric constant and trap energy level from the measured I-V vs temperature characteristics in the presence of air and hydrogen to show the validity of our postulations.

Vehicle energy throughput analysis as a drivetrain motor design aid

There are many variables to consider in the design of an electric motor. However, meeting the performance requirements for an electric vehicle drive may cause a designer to loose focus on its typical operation and hence fail to optimise the motor in the region where it processes the most power. This paper investigates operating requirements of electric vehicle motor drives using the University concept vehicle as an example. The paper outlines a methodology for determining primary operating region of a vehicle drive. The methodology is applied to standard driving cycles that are commonly used in the design and testing of vehicles.