Modal flexibility method for structural damage detection in suspension bridges

Suspension bridges meet the steadily growing demand for lighter and longer bridges in today’s infrastructure systems. These bridges are designed to have long life spans, but with age, their main cables and hangers could suffer from corrosion and fatigue. There is a need for a simple and reliable procedure to detect and locate such damage, so that appropriate retrofitting can be carried out to prevent bridge failure. Damage in a structure causes changes in its properties (mass, damping and stiffness) which in turn will cause changes in its vibration characteristics (natural frequencies, modal damping and mode shapes). Methods based on modal flexibility, which depends on both the natural frequencies and mode shapes, have the potential for damage detection. They have been applied successfully to beam and plate elements, trusses and simple structures in reinforced concrete and steel. However very limited applications for damage detection in suspension bridges have been identified to date. This paper examines the potential of modal flexibility methods for damage detection and localization of a suspension bridge under different damage scenarios in the main cables and hangers using numerical simulation techniques. Validated finite element model (FEM) of a suspension bridge is used to acquire mass normalized mode shape vectors and natural frequencies at intact and damaged states. Damage scenarios will be simulated in the validated FE models by varying stiffness of the damaged structural members. The capability of damage index based on modal flexibility to detect and locate damage is evaluated. Results confirm that modal flexibility based methods have the ability to successfully identify damage in suspension bridge main cables and hangers.

Detecting and Analyzing Linear Structures in Biomedical Images : A Case Study Using Corneal Nerve Fibers

Diabetic peripheral neuropathy (DPN) is one of the most common long-term complications of diabetes. The accurate detection and quantification of DPN are important for defining at-risk patients, anticipating deterioration, and assessing new therapies. Current methods of detecting and quantifying DPN, such as neurophysiology, lack sensitivity, require expert assessment and focus primarily on large nerve fibers. However, the earliest damage to nerve fibers in diabetic neuropathy is to the small nerve fibers. At present, small nerve fiber damage is currently assessed using skin/nerve biopsy; both are invasive technique and are not suitable for repeated investigations.

Quantitative stem-loop RT-PCR for detection of microRNAs

Plant microRNAs (miRNAs) are a class of endogenous small RNAs that are essential for plant development and survival. They arise from larger precursor RNAs with a characteristic hairpin structure and regulate gene activity by targeting mRNA transcripts for cleavage or translational repression. Efficient and reliable detection and quantification of miRNA expression has become an essential step in understanding their specific roles. The expression levels of miRNAs can vary dramatically between samples and they often escape detection by conventional technologies such as cloning, northern hybridization and microarray analysis. The stem-loop RT-PCR method described here is designed to detect and quantify mature miRNAs in a fast, specific, accurate and reliable manner. First, a miRNA-specific stem-loop RT primer is hybridized to the miRNA and then reverse transcribed. Next, the RT product is amplified and monitored in real time using a miRNA-specific forward primer and the universal reverse primer. This method enables miRNA expression profiling from as little as 10 pg of total RNA and is suitable for high-throughput miRNA expression analysis.

Radiographer commenting of trauma radiographs : a survey of the benefits, barriers and enablers to participation in an Australian healthcare setting

Introduction Radiographer abnormality detection systems that highlight abnormalities on trauma radiographs (‘red dot’ system) have been operating for more than 30 years. Recently, a number of pitfalls have been identified. These limitations initiated the evolution of a radiographer commenting system, whereby a radiographer provides a brief description of abnormalities identified in emergency healthcare settings. This study investigated radiographers' participation in abnormality detection systems, their perceptions of benefits, barriers and enablers to radiographer commenting, and perceptions of potential radiographer image interpretation services for emergency settings. Methods A cross-sectional survey was implemented. Participants included radiographers from four metropolitan hospitals in Queensland, Australia. Conventional descriptive statistics, histograms and thematic analysis were undertaken. Results Seventy-three surveys were completed and included in the analysis (68% response rate); 30 (41%) of respondents reported participating in abnormality detection in 20% or less of examinations, and 26(36%) reported participating in 80% or more of examinations. Five overarching perceived benefits of radiographer commenting were identified: assisting multidisciplinary teams, patient care, radiographer ability, professional benefits and quality of imaging. Frequently reported perceived barriers included ‘difficulty accessing image interpretation education’, ‘lack of time’ and ‘low confidence in interpreting radiographs’. Perceived enablers included ‘access to image interpretation education’ and ‘support from radiologist colleagues’. Conclusions A range of factors are likely to contribute to the successful implementation of radiographer commenting in addition to abnormality detection in emergency settings. Effective image interpretation education amenable to completion by radiographers would likely prove valuable in preparing radiographers for participation in abnormality detection and commenting systems in emergency settings.

Improving the detection of donations within the RHD negative blood donor panel which weakly express the RHD antigen

This project improved the detection and classification of very weakly expressed RhD variants in the Australian blood donor panel and contributed to the knowledge of anti-D reactivity patterns of RHD alleles that are undescribed. As such, the management of donations possessing these RHD alleles can be improved upon and the overall safety of transfusion medicine pertaining to the Rh blood group system will be increased. Future projects at ARCBS will be able to utilise the procedures developed in this project, thereby decreasing throughput time. The specificity of current testing will be improved and the need for outsourced RHD testing diminished.

Close-quarters Quadrotor flying for a pole inspection with position based visual servoing and high-speed vision

This paper presents a 100 Hz monocular position based visual servoing system to control a quadrotor flying in close proximity to vertical structures approximating a narrow, locally linear shape. Assuming the object boundaries are represented by parallel vertical lines in the image, detection and tracking is achieved using Plücker line representation and a line tracker. The visual information is fused with IMU data in an EKF framework to provide fast and accurate state estimation. A nested control design provides position and velocity control with respect to the object. Our approach is aimed at high performance on-board control for applications allowing only small error margins and without a motion capture system, as required for real world infrastructure inspection. Simulated and ground-truthed experimental results are presented.

Development of gas sensing technology for ground and airborne applications powered by solar energy : methodology and experimental results

Monitoring gases for environmental, industrial and agricultural fields is a demanding task that requires long periods of observation, large quantity of sensors, data management, high temporal and spatial resolution, long term stability, recalibration procedures, computational resources, and energy availability. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) are currently representing the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialised gas sensing systems, and offer the possibility of geo-located and time stamp samples. However, these technologies are not fully functional for scientific and commercial applications as their development and availability is limited by a number of factors: the cost of sensors required to cover large areas, their stability over long periods, their power consumption, and the weight of the system to be used on small UAVs. Energy availability is a serious challenge when WSN are deployed in remote areas with difficult access to the grid, while small UAVs are limited by the energy in their reservoir tank or batteries. Another important challenge is the management of data produced by the sensor nodes, requiring large amount of resources to be stored, analysed and displayed after long periods of operation. In response to these challenges, this research proposes the following solutions aiming to improve the availability and development of these technologies for gas sensing monitoring: first, the integration of WSNs and UAVs for environmental gas sensing in order to monitor large volumes at ground and aerial levels with a minimum of sensor nodes for an effective 3D monitoring; second, the use of solar energy as a main power source to allow continuous monitoring; and lastly, the creation of a data management platform to store, analyse and share the information with operators and external users. The principal outcomes of this research are the creation of a gas sensing system suitable for monitoring any kind of gas, which has been installed and tested on CH4 and CO2 in a sensor network (WSN) and on a UAV. The use of the same gas sensing system in a WSN and a UAV reduces significantly the complexity and cost of the application as it allows: a) the standardisation of the signal acquisition and data processing, thereby reducing the required computational resources; b) the standardisation of calibration and operational procedures, reducing systematic errors and complexity; c) the reduction of the weight and energy consumption, leading to an improved power management and weight balance in the case of UAVs; d) the simplification of the sensor node architecture, which is easily replicated in all the nodes. I evaluated two different sensor modules by laboratory, bench, and field tests: a non-dispersive infrared module (NDIR) and a metal-oxide resistive nano-sensor module (MOX nano-sensor). The tests revealed advantages and disadvantages of the two modules when used for static nodes at the ground level and mobile nodes on-board a UAV. Commercial NDIR modules for CO2 have been successfully tested and evaluated in the WSN and on board of the UAV. Their advantage is the precision and stability, but their application is limited to a few gases. The advantages of the MOX nano-sensors are the small size, low weight, low power consumption and their sensitivity to a broad range of gases. However, selectivity is still a concern that needs to be addressed with further studies. An electronic board to interface sensors in a large range of resistivity was successfully designed, created and adapted to operate on ground nodes and on-board UAV. The WSN and UAV created were powered with solar energy in order to facilitate outdoor deployment, data collection and continuous monitoring over large and remote volumes. The gas sensing, solar power, transmission and data management systems of the WSN and UAV were fully evaluated by laboratory, bench and field testing. The methodology created to design, developed, integrate and test these systems was extensively described and experimentally validated. The sampling and transmission capabilities of the WSN and UAV were successfully tested in an emulated mission involving the detection and measurement of CO2 concentrations in a field coming from a contaminant source; the data collected during the mission was transmitted in real time to a central node for data analysis and 3D mapping of the target gas. The major outcome of this research is the accomplishment of the first flight mission, never reported before in the literature, of a solar powered UAV equipped with a CO2 sensing system in conjunction with a network of ground sensor nodes for an effective 3D monitoring of the target gas. A data management platform was created using an external internet server, which manages, stores, and shares the data collected in two web pages, showing statistics and static graph images for internal and external users as requested. The system was bench tested with real data produced by the sensor nodes and the architecture of the platform was widely described and illustrated in order to provide guidance and support on how to replicate the system. In conclusion, the overall results of the project provide guidance on how to create a gas sensing system integrating WSNs and UAVs, how to power the system with solar energy and manage the data produced by the sensor nodes. This system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, zoology, and botanical studies opening the way to an ubiquitous low cost environmental monitoring, which may help to decrease our carbon footprint and to improve the health of the planet.

Electrochemical current rectification – a novel signal amplification strategy for highly sensitive and selective aptamer-based biosensor

Electrochemical aptamer-based (E-AB) sensors represent an emerging class of recently developed sensors. However, numerous of these sensors are limited by a low surface density of electrode-bound redox-oligonucleotides which are used as probe. Here we propose to use the concept of electrochemical current rectification (ECR) for the enhancement of the redox signal of E-AB sensors. Commonly, the probe-DNA performs a change in conformation during target binding and enables a nonrecurring charge transfer between redox-tag and electrode. In our system, the redox-tag of the probe-DNA is continuously replenished by solution-phase redox molecules. A unidirectional electron transfer from electrode via surface-linked redox-tag to the solution-phase redox molecules arises that efficiently amplifies the current response. Using this robust and straight-forward strategy, the developed sensor showed a substantial signal amplification and consequently improved sensitivity with a calculated detection limit of 114 nM for ATP, which was improved by one order of magnitude compared with the amplification-free detection and superior to other previous detection results using enzymes or nanomaterials-based signal amplification. To the best of our knowledge, this is the first demonstration of an aptamer-based electrochemical biosensor involving electrochemical rectification, which can be presumably transferred to other biomedical sensor systems.

Regulation, compliance and the Australian forensic accounting profession

Legacies of the Global Financial Crisis and major domestic corporate collapses – such as HIH Insurance Pty Ltd and One.Tel Ltd (telecommunications) – have significantly changed Australia‟s financial regulatory landscape. Legal requirements for auditors have attracted particular attention as have practice standards more broadly around disclosure and conflict of interest. Conversely, although successful detection and prosecution of breaches may rest in significant part on forensic accounting activities, Australia‟s practitioners in this field have no minimum training or qualifications standards other than the baseline requirements mandated by the country‟s three professional accounting bodies. For those unaffiliated with these organizations, no professional oversight exists. In Australia, growth in the forensic accounting industry has been in direct response to public demand for expertise in a broad range of fraud, forensic and business analytics areas in order to improve the corporate governance practices of Australian organizations. During the 1990s, Australian forensic accounting firms expanded and diversified into a number of different areas going well beyond just the examination of financial documents and involvement in financial litigation disputes. “Big 4” accounting firms such as PriceWaterhouseCoopers, KPMG, Deloitte and Ernst and Young formed independent forensic accounting or forensic services units; a number of mid-tier and „boutique‟ forensic accounting firms similarly expanded into forensic investigative, analytical and advisory services. By 2008, 800 forensic accountants were registered with the country‟s largest specialist forensic accounting group, the Forensic Accounting Special Interest Group (FASIG) of the ICAA1. Currently, obtaining more precise figures on numbers of forensic accounting practitioners is problematic: professional accounting bodies either do not keep a register or have ceased registering their forensic accounting members; lack of formal recognition, admission or certification processes complicate identification of candidates; and diversity of the skills sets the industry requires has meant the influx of non-accounting based specialists.

Differential effects of refractive blur on day and night-time driving performance

Purpose To investigate the effect of different levels of refractive blur on real-world driving performance measured under day and nighttime conditions. Methods Participants included 12 visually normal, young adults (mean age = 25.8 ± 5.2 years) who drove an instrumented research vehicle around a 4 km closed road circuit with three different levels of binocular spherical refractive blur (+0.50 diopter sphere [DS], +1.00 DS, +2.00 DS) compared with a baseline condition. The subjects wore optimal spherocylinder correction and the additional blur lenses were mounted in modified full-field goggles; the order of testing of the blur conditions was randomized. Driving performance was assessed in two different sessions under day and nighttime conditions and included measures of road signs recognized, hazard detection and avoidance, gap detection, lane-keeping, sign recognition distance, speed, and time to complete the course. Results Refractive blur and time of day had significant effects on driving performance (P < 0.05), where increasing blur and nighttime driving reduced performance on all driving tasks except gap judgment and lane keeping. There was also a significant interaction between blur and time of day (P < 0.05), such that the effects of blur were exacerbated under nighttime driving conditions; performance differences were evident even for +0.50 DS blur relative to baseline for some measures. Conclusions The effects of blur were greatest under nighttime conditions, even for levels of binocular refractive blur as low as +0.50 DS. These results emphasize the importance of accurate and up-to-date refractive correction of even low levels of refractive error when driving at night.

The relationship between emotional intelligence and depression in a clinical sample

Background and Objectives: Although depression is a commonly occurring mental illness, research concerning strategies for early detection and prophylaxis has not until now focused on the possible utility of measures of Emotional Intelligence (EI) as a potential predictive factor. The current study aimed to investigate the relationship between EI and a clinical diagnosis of depression in a cohort of adults. Methods: Sixty-two patients (59.70% female) with a DSM-IV-TR diagnosis of a major affective disorder and 39 aged matched controls (56.40% female) completed self-report instruments assessing EI and depression in a cross-sectional study. Results: Significant associations were observed between severity of depression and the EI dimensions of Emotional Management (r = -0.56) and Emotional Control (r = -0.62). The results show a reduced social involvement, an increased prior institutionalization and an increased incidence of "Schizophrenic Psychosis" and "Abnormal Personalities" in the sub-group of repeated admissions. Conclusions: Measures of EI may have predictive value in terms of early identification of those at risk for developing depression. The current study points to the potential value of conducting further studies of a prospective nature.

Toward a model for predicting magnetic susceptibility of bedrock regolith and soils

One of the Department of Defense's most pressing environmental problems is the efficient detection and identification of unexploded ordnance (UXO). In regions of highly magnetic soils, magnetic and electromagnetic sensors often detect anomalies that are of geologic origin, adding significantly to remediation costs. In order to develop predictive models for magnetic susceptibility, it is crucial to understand modes of formation and the spatial distribution of different iron oxides. Most rock types contain iron and their magnetic susceptibility is determined by the amount and form of iron oxides present. When rocks weather, the amount and form of the oxides change, producing concomitant changes in magnetic susceptibility. The type of iron oxide found in the weathered rock or regolith is a function of the duration and intensity of weathering, as well as the original content of iron in the parent material. The rate of weathering is controlled by rainfall and temperature; thus knowing the climate zone, the amount of iron in the lithology and the age of the surface will help predict the amount and forms of iron oxide. We have compiled analyses of the types, amounts, and magnetic properties of iron oxides from soils over a wide climate range, from semi arid grasslands, to temperate regions, and tropical forests. We find there is a predictable range of iron oxide type and magnetic susceptibility according to the climate zone, the age of the soil and the amount of iron in the unweathered regolith.

Prevalence of methicillin resistance and virulence determinants of Staphylococcus aureus in diabetic foot ulcers

Background Diabetic foot ulceration (DFU) is a multifactorial process and is responsible for considerable morbidity and contributes to the increasing cost of health care worldwide. The diagnosis and identification of these ulcers remains a complex problem. Bacterial infection is promoted in the diabetic foot wound by decreased vascular supply and impaired host immune response. As conventional clinical microbiological methods are time-consuming and only identifies about 1% of the wound microbiota, detection of bacteria present in DFUs using molecular methods is highly advantageous and efficient. The aim of this study was to assess the virulence and methicillin resistance profiles of Staphylococcus aureus detected in DFUs using DNA-based methods. Methods A total of 223 swab samples were collected from 30 patients from March to October 2012. Bacterial DNA was extracted from the swab samples using standard procedures and was used to perform polymerase chain reaction (PCR) using specific oligonucleotide primers. The products were visualized using agarose gel electrophoresis. Results S. aureus was detected in 44.8% of samples. 25% of the S. aureus was methicillin-resistant S. aureus harboring the mecA gene. The alpha-toxin gene was present in 85% of the S. aureus positive samples. 61% of the S. aureus present in DFU samples harbored the exfoliatin factor A gene. Both the fibronectin factor A and fibronectin factor B gene were detected in 71% and 74% of the S. aureus positive samples. Conclusions DNA-based detection and characterization of bacteria in DFUs are rapid and efficient and can assist in accurate, targeted antibiotic therapy of DFU infections. The majority of S. aureus detected in this study were highly virulent and also resistant to methicillin. Further studies are required to understand the role of S. aureus in DFU trajectory.

Kallikrein 4 (hK4) and prostate-specific antigen (PSA) are associated with the loss of E-cadherin and an epithelial-mesenchymal transition (EMT)-like effect in prostate cancer cells

Prostate-specific antigen (PSA) and the related kallikrein family of serine proteases are current or emerging biomarkers for prostate cancer detection and progression. Kallikrein 4 (KLK4/hK4) is of particular interest, as KLK4 mRNA has been shown to be elevated in prostate cancer. In this study, we now show that the comparative expression of hK4 protein in prostate cancer tissues, compared with benign glands, is greater than that of PSA and kallikrein 2 (KLK2/hK2), suggesting that hK4 may play an important functional role in prostate cancer progression in addition to its biomarker potential. To examine the roles that hK4, as well as PSA and hK2, play in processes associated with progression, these kallikreins were separately transfected into the PC-3 prostate cancer cell line, and the consequence of their stable transfection was investigated. PC-3 cells expressing hK4 had a decreased growth rate, but no changes in cell proliferation were observed in the cells expressing PSA or hK2. hK4 and PSA, but not hK2, induced a 2.4-fold and 1.7-fold respective increase, in cellular migration, but not invasion, through Matrigel, a synthetic extracellular matrix. We hypothesised that this increase in motility displayed by the hK4 and PSA-expressing PC-3 cells may be related to the observed change in structure in these cells from a typical rounded epithelial-like cell to a spindle-shaped, more mesenchymal-like cell, with compromised adhesion to the culture surface. Thus, the expression of E-cadherin and vimentin, both associated with an epithelial-mesenchymal transition (EMT), was investigated. E-cadherin protein was lost and mRNA levels were significantly decreased in PC-3 cells expressing hK4 and PSA (10-fold and 7-fold respectively), suggesting transcriptional repression of E-cadherin, while the expression of vimentin was increased in these cells. The loss of E-cadherin and associated increase in vimentin are indicative of EMT and provides compelling evidence that hK4, in particular, and PSA have a functional role in the progression of prostate cancer through their promotion of tumour cell migration.