Research outcomes for improved management of insulated rail joints

Insulated Rail Joints (IRJs) are safety critical component of the automatic block signalling and broken rail detection systems. IRJs exhibit several failure modes due to complex interaction between the railhead ends and the wheel tread near the gap. These localised zones could not be monitored using automatic sensing devices and hence are resorted to visual inspection only, which is error prone and expensive. In Australia alone currently there are 50,000 IRJs across 80,000 km of rail track. The significance of the problem around the world could thus be realised as there exists one IRJ for each 1.6 km track length. IRJs exhibit extremely low and variable service life; further the track substructure underneath IRJs degrade faster. Thus presence of the IRJs incur significant costs to track maintenance. IRJ failures have also contributed to some train derailments and various traffic disruptions in rail lines. This paper reports a systematic research carried out over seven years on the mechanical behaviour of IRJs for practically relevant outcomes. The research has scientifically established that stiffening the track bed for reduction in impact force is an ill-conceived concept and the most effective method is to reduce the gap size. Further it is established that hardening the railhead ends through laser coating (or other) cannot adequately address the metal flow problem in the long run; modification of the railhead profile is the only appropriate technique to completely eliminate the problem. Part of these outcomes has been adopted by the rail infrastructure owners in Australia.

4D deformation modeling of cortical disease progression in Alzheimer's dementia

This work describes the development of a model of cerebral atrophic changes associated with the progression of Alzheimer's disease (AD). Linear registration, region-of-interest analysis, and voxel-based morphometry methods have all been employed to elucidate the changes observed at discrete intervals during a disease process. In addition to describing the nature of the changes, modeling disease-related changes via deformations can also provide information on temporal characteristics. In order to continuously model changes associated with AD, deformation maps from 21 patients were averaged across a novel z-score disease progression dimension based on Mini Mental State Examination (MMSE) scores. The resulting deformation maps are presented via three metrics: local volume loss (atrophy), volume (CSF) increase, and translation (interpreted as representing collapse of cortical structures). Inspection of the maps revealed significant perturbations in the deformation fields corresponding to the entorhinal cortex (EC) and hippocampus, orbitofrontal and parietal cortex, and regions surrounding the sulci and ventricular spaces, with earlier changes predominantly lateralized to the left hemisphere. These changes are consistent with results from post-mortem studies of AD.

Education policy-making and time

This paper examines the global policy convergence toward high-stakes testing in schools and the use of test results to ‘steer at a distance’, particularly as it applies to policy-makers’ promise to improve teacher quality. Using Deleuze’s three syntheses of time in the context of the Australian policy blueprint Quality Education, this paper argues that using test scores to discipline teaching repeats the past habit of policy-making as continuing the problem of the unaccountable teacher. This results in local policy-making enfolding test scores in a pure past where the teacher-as-problem is resolved through the use of data from testing to deliver accountability and transparency. This use of the database returns a digitised form of inspection that is a repetition of the habit of teacher-as-problem. While dystopian possibilities are available through the database, in what Deleuze refers to as a control society, for us the challenge is to consider policy-making as a step into an unknown future, to engage with producing policy that is not grounded on the unconscious interiority of solving the teacher problem, but of imagining new ways of conceiving the relationship between policy-making and teaching.

A decision support framework for prioritization of engineering asset management activities under uncertainty

Engineers and asset managers must often make decisions on how to best allocate limited resources amongst different interrelated activities, including repair, renewal, inspection, and procurement of new assets. The presence of project interdependencies and the lack of sufficient information on the true value of an activity often produce complex problems and leave the decision maker guessing about the quality and robustness of their decision. In this paper, a decision support framework for uncertain interrelated activities is presented. The framework employs a methodology for multi-criteria ranking in the presence of uncertainty, detailing the effect that uncertain valuations may have on the priority of a particular activity. The framework employs employing semi-quantitative risk measures that can be tailored to an organisation and enable a transparent and simple-to-use uncertainty specification by the decision maker. The framework is then demonstrated on a real world project set from a major Australian utility provider.

Inside the black box of food safety: A qualitative study of ‘non-compliance’ among food businesses

Issue addressed The paper examines the meanings of food safety among food businesses deemed non-compliant and considers the need for an ‘insider perspective’ to inform a more nuanced health promotion practice. Methods In-depth interviews were conducted with 29 food business operators who had been recently deemed ‘non-compliant’ through Council inspection. Result Paradoxically, these ‘non-compliers’ revealed a strong belief in the importance of food safety as well as a desire to comply with the regulations as communicated to them by Environmental Health Officers (EHOs). Conclusions The evidence base of food safety is largely informed by the science of food hazards, yet there is a very important need to illuminate the ‘insider’ experience of food businesses doing food safety on a daily basis. This requires a more socially nuanced appreciation of food businesses beyond the simple dichotomy of compliant/ non-compliant. So what? Armed with a deeper understanding of the social context surrounding food safety practice, it is anticipated that a more balanced, collaborative mode of food safety health promotion could develop which could add to the current signature model of regulation.

A systematic review of axillary web syndrome (AWS)

Introduction Axillary web syndrome (AWS) can result in early post-operative and long-term difficulties following lymphadenectomy for cancer and should be recognised by clinicians. This systematic review was conducted to synthesise information on AWS clinical presentation and diagnosis, frequency, natural progression, grading, pathoaetiology, risk factors, symptoms, interventions and outcomes. Methods Electronic searches were conducted using Cochrane, Pubmed, MEDLINE, CINAHL, EMBASE, AMED, PEDro and Google Scholar until June 2013. The methodological quality of included studies was determined using the Downs and Black checklist. Narrative synthesis of results was undertaken. Results Thirty-seven studies with methodological quality scores ranging from 11 to 26 on a 28-point scale were included. AWS diagnosis relies on inspection and palpation; grading has not been validated. AWS frequency was reported in up to 85.4 % of patients. Biopsies identified venous and lymphatic pathoaetiology with five studies suggesting lymphatic involvement. Twenty-one studies reported AWS occurrence within eight post-operative weeks, but late occurrence of greater than 3 months is possible. Pain was commonly reported with shoulder abduction more restricted than flexion. AWS symptoms usually resolve within 3 months but may persist. Risk factors may include extensiveness of surgery, younger age, lower body mass index, ethnicity and healing complications. Low-quality studies suggest that conservative approaches including analgesics, non-steroidal anti-inflammatory drugs and/or physiotherapy may be safe and effective for early symptom reduction. Conclusions AWS appears common. Current evidence for the treatment of AWS is insufficient to provide clear guidance for clinical practice. Implications for Cancer Survivors Cancer survivors should be informed about AWS. Further investigation is needed into pathoaetiology, long-term outcomes and to determine effective treatment using standardised outcomes.

Agreement between physiotherapists rating scapular posture in multiple planes in patients with neck pain: Reliability study

Objective Evaluation of scapular posture is an integral component of the clinical assessment of painful neck disorders. The aim of this study was to evaluate agreement between therapist judgements of scapula posture in multiple biomechanical planes in individuals with neck pain. Design Inter-therapist reliability study. Setting Research laboratory. Participants Fifteen participants with chronic neck pain. Main outcome measures Four physiotherapists recorded ratings of scapular orientation (relative to the thorax) in five different scapula postural planes (plane of scapula, sagittal plane, transverse plane, horizontal plane, and vertical plane) under four test conditions (at rest, and during three isometric shoulder conditions) in all participants. Inter-therapist reliability was expressed using both generalized and paired kappa coefficient. Results Following adjustment for expected agreement and the high prevalence of neutral ratings (81%), on average both the generalised kappa (0.37) as well as Cohen's Kappa for the two therapist pairs (0.45 and 0.42) demonstrated only slight to moderate inter-therapist reliability. Conclusions The findings suggest that ratings of scapular posture in individuals with neck pain by visual inspection has only slight to moderate reliability and should only be used in conjunction with other clinical tests when judging scapula function in these patients.

Socio-cultural influences on vehicle defects in the Omani heavy vehicle industry

With recent economic growth in Oman there is increased use of heavy vehicles, presenting an increase in heavy vehicle crashes, associated fatalities and injuries. Vehicle defects cause a significant number of heavy vehicle crashes in Oman and increase the likelihood of fatalities. The aim of this study is to explore factors contributing to driving with vehicle defects in the Omani heavy vehicle industry. A series of qualitative participants observations were conducted in Oman with 49 drivers. These observations also involved discussion and interviews with drivers. The observations occurred at two road-side locations where heavy vehicle drivers gather for eating, resting, vehicle check-up, etc. Data collection was conducted over a three week period. The data was analysed using thematic analysis. A broad number of factors were identified as contributing to the driving of vehicles with defects. Participants indicated that tyres and vehicle mechanical faults were a common issue in the heavy vehicle industry. Participants regularly reported that their companies use cheap, poor quality standards parts and conducted minimal maintenance. Drivers also indicated that they felt powerless to resist company pressure to drive vehicles with known faults. In addition, drivers reported that traffic police were generally in effective and lacked skill to appropriately conduct roadside inspection on trucks. Further, participants stated that it was possible for companies to avoid being fined during annual or roadside vehicle inspections if members of the company knew the traffic police officer conducting the inspection. Moreover, fines issued by police are generally directed to the individual driver rather than being applied to the company, thus providing no incentive for companies to address vehicle faults. The implications of the findings are discussed.

Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

Application of image processing techniques for frog call classification

Frogs have received increasing attention due to their effectiveness for indicating the environment change. Therefore, it is important to monitor and assess frogs. With the development of sensor techniques, large volumes of audio data (including frog calls) have been collected and need to be analysed. After transforming the audio data into its spectrogram representation using short-time Fourier transform, the visual inspection of this representation motivates us to use image processing techniques for analysing audio data. Applying acoustic event detection (AED) method to spectrograms, acoustic events are firstly detected from which ridges are extracted. Three feature sets, Mel-frequency cepstral coefficients (MFCCs), AED feature set and ridge feature set, are then used for frog call classification with a support vector machine classifier. Fifteen frog species widely spread in Queensland, Australia, are selected to evaluate the proposed method. The experimental results show that ridge feature set can achieve an average classification accuracy of 74.73% which outperforms the MFCCs (38.99%) and AED feature set (67.78%).

Health Assessment and Physical Examination, 2nd Edition

Health Assessment and Physical Examination is designed to teach students to assess a patient’s physical, psychological, cultural and emotional dimensions of health as a foundation of nursing care. The skills of interviewing, inspection, percussion, palpation, auscultation, and documentation are refined to help students to make clinical judgements and promote healthy patient outcomes. A strong emphasis on science encompasses all the technical aspects of anatomy, physiology, and assessment, while highlighting clinically relevant information. Emphasis on caring is displayed through themes of assessment of the whole person, which also encourages nurses to think about care for themselves as well as patients.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

Influence of Elastic-Constants on Mode-I Stress-Intensity Factors in 3-Dimensional Crack Problems

Plates with V-through edge notches subjected to pure bending and specimens with rectangular edge-through-notches subjected to combined bending and axial pull were investigated (under live-load and stress-frozen conditions) in a completely nondestructive manner using scattered-light photoelasticity. Stress-intensity factors (SIFs) were evaluated by analysing the singular stress distributions near crack-tips. Improved methods are suggested for the evaluation of SIFs. The thickness-wise variation of SIFs is also obtained in the investigation. The results obtained are compared with the available theoretical solutions.

A sampling technique for two-spotted mite in papaya

Two-spotted mite, Tetranychus urticae Koch, was until recently regarded as a minor and infrequent pest of papaya in Queensland through the dry late winter/early summer months. The situation has changed over the past 4-5 years, so that now some growers consider spider mites significant pests all year round. This altered pest status corresponded with a substantial increase in the use of fungicides to control black spot (Asperisporium caricae). A project was initiated in 1998 to examine the potential reasons for escalating mite problems in commercially-grown papaya, which included regular sampling over a 2 year period for mites, mite damage and beneficial arthropods on a number of farms on the wet tropical coast and drier Atherton Tableland. Differences in soil type, papaya variety, chemical use and some agronomic practices were included in this assessment. Monthly visits were made to each site where 20 randomly-selected plants from each of 2 papaya lines (yellow and red types) were surveyed. Three leaves were selected from each plant, one from each of the bottom, middle and top strata of leaves. The numbers of mobile predators were recorded, along with visual estimates of the percentage and age of mite damage on each leaf. Leaves were then sprayed with hairspray to fix the mites and immature predators to the leaf surface. Four leaf disks, 25 mm in diameter, were then punched from each leaf into a 50 ml storage container with a purpose-built disk-cutting tool. Disks from each leaf position were separated by tissue paper, within the container. On return to the laboratory, each leaf disk was scrutinised under a binocular microscope to determine the numbers of two-spotted mites and eggs, predatory mites and eggs, and the immature stages of predatory insects (mainly Stethorus, Halmus and lacewings). A total of 2160 leaf disks have been examined each month. All data have been entered into an Access database to facilitate comparisons between sites.

The mycotoxins 4-deoxynivalenol, zearalenone and aflatoxin in weather-damaged wheat harvested 1983-1985 in south-east Queensland

A survey for various mycotoxins was carried out on samples of all wheat delivered to nine storage and marketing depots in south-eastern Queensland, selected as most likely to receive mycotoxin-contaminated grain. All wheat was surveyed during 1983, when the degree of weather damage was high. Samples of the poorest grade of wheat from these depots were also surveyed in 1984 and 1985. The surveys included all regions where head scab of wheat caused by Fusariurn graminearurn Schwabe Group 2 had been reported to occur at significant levels. 4-Deoxynivalenol was detected in nearly all pooled samples representing bulk wheat at concentrations ranging from traces of <0.01 up to 1.7 mg kg-1. The highest concentration of zearlenone detected in a pooled wheat sample was 0.04 mg kg-1. In a few samples representing individual wheat deliveries and with up to 2.8% by weight of pink grains, 4-deoxynivalenol concentrations ranged up to 11.7 mg kg-' and zearalenone up to 0.43 mg kg-l. Aflatoxins B,, B2, G1 and G2 were detected in only one pooled sample of wheat, at a total aflatoxin concentration of 0.003 mg kg-'. Ochratoxin A, sterigmatocystin and T-2 toxin were not detected. Higher concentrations of mycotoxins were found in the poorer grades of wheat.