Ship Seakeeping Operability, Motion Control, and Autonomy - A Bayesian Perspective

Ship seakeeping operability refers to the quantification of motion performance in waves relative to mission requirements. This is used to make decisions about preferred vessel designs, but it can also be used as comprehensive assessment of the benefits of ship-motion-control systems. Traditionally, operability computation aggregates statistics of motion computed over over the envelope of likely environmental conditions in order to determine a coefficient in the range from 0 to 1 called operability. When used for assessment of motion-control systems, the increase of operability is taken as the key performance indicator. The operability coefficient is often given the interpretation of the percentage of time operable. This paper considers an alternative probabilistic approach to this traditional computation of operability. It characterises operability not as a number to which a frequency interpretation is attached, but as a hypothesis that a vessel will attain the desired performance in one mission considering the envelope of likely operational conditions. This enables the use of Bayesian theory to compute the probability of that this hypothesis is true conditional on data from simulations. Thus, the metric considered is the probability of operability. This formulation not only adheres to recent developments in reliability and risk analysis, but also allows incorporating into the analysis more accurate descriptions of ship-motion-control systems since the analysis is not limited to linear ship responses in the frequency domain. The paper also discusses an extension of the approach to the case of assessment of increased levels of autonomy for unmanned marine craft.

MRI-based strain and strain rate analysis of left ventricle: A modified hierarchical transformation model

Background Different from other indicators of cardiac function, such as ejection fraction and transmitral early diastolic velocity, myocardial strain is promising to capture subtle alterations that result from early diseases of the myocardium. In order to extract the left ventricle (LV) myocardial strain and strain rate from cardiac cine-MRI, a modified hierarchical transformation model was proposed. Methods A hierarchical transformation model including the global and local LV deformations was employed to analyze the strain and strain rate of the left ventricle by cine-MRI image registration. The endocardial and epicardial contour information was introduced to enhance the registration accuracy by combining the original hierarchical algorithm with an Iterative Closest Points using Invariant Features algorithm. The hierarchical model was validated by a normal volunteer first and then applied to two clinical cases (i.e., the normal volunteer and a diabetic patient) to evaluate their respective function. Results Based on the two clinical cases, by comparing the displacement fields of two selected landmarks in the normal volunteer, the proposed method showed a better performance than the original or unmodified model. Meanwhile, the comparison of the radial strain between the volunteer and patient demonstrated their apparent functional difference. Conclusions The present method could be used to estimate the LV myocardial strain and strain rate during a cardiac cycle and thus to quantify the analysis of the LV motion function.

Normalized wall index specific and MRI-based stress analysis of atherosclerotic carotid plaques: A study comparing acutely symptomatic and asymptomatic patients

Background: Biomechanical stresses play an important role in determining plaque stability. Quantification of these simulated stresses can be potentially used to assess plaque vulnerability and differentiate different patient groups. Methods and Results: 54 asymptomatic and 45 acutely symptomatic patients underwent in vivo multicontrast magnetic resonance imaging (MRI) of the carotid arteries. Plaque geometry used for finite element analysis was derived from in vivo MRI at the sites of maximum and minimum plaque burden. In total, 198 slices were used for the computational simulations. A pre-shrink technique was used to refine the simulation. Maximum principle stress at the vulnerable plaque sites (ie, critical stress) was extracted for the selected slices and a comparison was performed between the 2 groups. Critical stress in the slice with maximum plaque burden is significantly higher in acutely symptomatic patients as compared to asymptomatic patients (median, inter quartile range: 198.0 kPa (119.8-359.0 kPa) vs 138.4 kPa (83.8-242.6 kPa), P=0.04). No significant difference was found in the slice with minimum plaque burden between the 2 groups (196.7 kPa (133.3-282.7 kPa) vs 182.4 kPa (117.2-310.6 kPa), P=0.82). Conclusions: Acutely symptomatic carotid plaques have significantly high biomechanical stresses than asymptomatic plaques. This might be potentially useful for establishing a biomechanical risk stratification criteria based on plaque burden in future studies.

Association between biomechanical structural stresses of atherosclerotic carotid plaques and subsequent ischaemic cerebrovascular events - A longitudinal in vivo magnetic resonance imaging-based finite element study

Background: High-resolution magnetic resonance (MR) imaging has been used for MR imaging-based structural stress analysis of atherosclerotic plaques. The biomechanical stress profile of stable plaques has been observed to differ from that of unstable plaques; however, the role that structural stresses play in determining plaque vulnerability remains speculative. Methods: A total of 61 patients with previous history of symptomatic carotid artery disease underwent carotid plaque MR imaging. Plaque components of the index artery such as fibrous tissue, lipid content and plaque haemorrhage (PH) were delineated and used for finite element analysis-based maximum structural stress (M-C Stress) quantification. These patients were followed up for 2 years. The clinical end point was occurrence of an ischaemic cerebrovascular event. The association of the time to the clinical end point with plaque morphology and M-C Stress was analysed. Results: During a median follow-up duration of 514 days, 20% of patients (n=12) experienced an ischaemic event in the territory of the index carotid artery. Cox regression analysis indicated that M-C Stress (hazard ratio (HR): 12.98 (95% confidence interval (CI): 1.32-26.67, pZ0.02), fibrous cap (FC) disruption (HR: 7.39 (95% CI: 1.61e33.82), p Z 0.009) and PH (HR: 5.85 (95% CI: 1.27e26.77), p Z 0.02) are associated with the development of subsequent cerebrovascular events. Plaques associated with future events had higher M-C Stress than those which had remained asymptomatic (median (interquartile range, IQR): 330 kPa (229e494) vs. 254 kPa (166-290), p Z0.04). Conclusions: High biomechanical structural stresses, in addition to FC rupture and PH, are associated with subsequent cerebrovascular events.

Structural and functional characterization of dendritic arbors and GABAergic synaptic inputs on interneurons and principal cells in the rat basolateral amygdala

The basolateral amygdala (BLA) is a complex brain region associated with processing emotional states, such as fear, anxiety, and stress. Some aspects of these emotional states are driven by the network activity of synaptic connections, derived from both local circuitry and projections to the BLA from other regions. Although the synaptic physiology and general morphological characteristics are known for many individual cell types within the BLA, the combination of morphological, electrophysiological, and distribution of neurochemical GABAergic synapses in a three-dimensional neuronal arbor has not been reported for single neurons from this region. The aim of this study was to assess differences in morphological characteristics of BLA principal cells and interneurons, quantify the distribution of GABAergic neurochemical synapses within the entire neuronal arbor of each cell type, and determine whether GABAergic synaptic density correlates with electrophysiological recordings of inhibitory postsynaptic currents. We show that BLA principal neurons form complex dendritic arborizations, with proximal dendrites having fewer spines but higher densities of neurochemical GABAergic synapses compared with distal dendrites. Furthermore, we found that BLA interneurons exhibited reduced dendritic arbor lengths and spine densities but had significantly higher densities of putative GABAergic synapses compared with principal cells, which was correlated with an increased frequency of spontaneous inhibitory postsynaptic currents. The quantification of GABAergic connectivity, in combination with morphological and electrophysiological measurements of the BLA cell types, is the first step toward a greater understanding of how fear and stress lead to changes in morphology, local connectivity, and/or synaptic reorganization of the BLA.

Micro-CT based characterisation of changes to the vascular network following closed soft tissue trauma and cryotherapy

This project has investigated how the architecture of the blood vessels supplying nutrients to skeletal muscles is affected by muscle contusion injuries, and how it changes during healing with or without initial treatment of the injury by icing. In order to do this, we used contrast agents to visualise blood vessels in 3D with micro-computed tomography imaging. This research significantly contributes to the fields of orthopaedics, traumatology and sports medicine, as it improves our understanding of muscle contusion injuries. Furthermore, the methods developed in this thesis may help to improve the diagnosis and monitoring of these injuries.

Mineralogical and metallurgical examination of fluorosilicate mineral floatation in the Ok Tedi circuit

The Ok Tedi copper orebody consists of porphyry and skarn orebodies. The skarn orebodies, identified by different mineralogy, are the source of high intermittent fluorine levels in the mill concentrates. This paper discusses the results of the work undertaken to characterize the various fluorine-bearing minerals in samples of final copper concentrates and the distribution of fluorine amongst the minerals. Quantification of each mineral in mill feed and various flotation streams at Ok Tedi enables an understanding of the quantitative response of fluorine-bearing minerals to flotation. The metallurgical behavior of fluorine in the flotation process is also discussed.

Time evolution of graphene growth on SiC as a function of annealing temperature

We followed by X-ray Photoelectron Spectroscopy (XPS) the time evolution of graphene layers obtained by annealing 3C SiC(111)/Si(111) crystals at different temperatures. The intensity of the carbon signal provides a quantification of the graphene thickness as a function of the annealing time, which follows a power law with exponent 0.5. We show that a kinetic model, based on a bottom-up growth mechanism, provides a full explanation to the evolution of the graphene thickness as a function of time, allowing to calculate the effective activation energy of the process and the energy barriers, in excellent agreement with previous theoretical results. Our study provides a complete and exhaustive picture of Si diffusion into the SiC matrix, establishing the conditions for a perfect control of the graphene growth by Si sublimation.

Circulating tumor cells: Isolation, expansion, characterization and translation to clinic

Circulating tumor cells (CTCs) are the seeds for cancer metastases development, which is responsible for >90% of cancer-related deaths. Accurate quantification of CTCs in human fluids could be an invaluable tool for understanding cancer prognosis, delivering personalized medicine to prevent metastasis and finding cancer therapy effectiveness. Although CTCs were first discovered more than 200 years ago, until now it has been a nightmare for clinical practitioners to capture and diagnose CTCs in clinical settings. Our society needs rapid, sensitive, and reliable assays to identify the CTCs from blood in order to help save millions of lives. Due to the phenotypic EMT transition, CTCs are undetected for more than one-third of metastatic breast cancer patients in clinics. To tackle the above challenges, the first volume in “Circulating Tumor Cells (CTCs): Detection Methods, Health Impact and Emerging Clinical Challenges discusses recent developments of different technologies, which have the capability to target and elucidate the phenotype heterogenity of CTCS. It contains seven chapters written by world leaders in this area, covering basic science to possible device design which can have beneficial applications in society. This book is unique in its design and content, providing an in-depth analysis to elucidate biological mechanisms of cancer disease progression, CTC detection challenges, possible health effects and the latest research on evolving technologies which have the capability to tackle the above challenges. It describes the broad range of coverage on understanding CTCs biology from early predictors of the metastatic spread of cancer, new promising technology for CTC separation and detection in clinical environment and monitoring therapy efficacy via finding the heterogeneous nature of CTCs. (Imprint: Nova Biomedical)

A data fusion approach of multiple maintenance data sources for real-world reliability modelling

A central tenet in the theory of reliability modelling is the quantification of the probability of asset failure. In general, reliability depends on asset age and the maintenance policy applied. Usually, failure and maintenance times are the primary inputs to reliability models. However, for many organisations, different aspects of these data are often recorded in different databases (e.g. work order notifications, event logs, condition monitoring data, and process control data). These recorded data cannot be interpreted individually, since they typically do not have all the information necessary to ascertain failure and preventive maintenance times. This paper presents a methodology for the extraction of failure and preventive maintenance times using commonly-available, real-world data sources. A text-mining approach is employed to extract keywords indicative of the source of the maintenance event. Using these keywords, a Naïve Bayes classifier is then applied to attribute each machine stoppage to one of two classes: failure or preventive. The accuracy of the algorithm is assessed and the classified failure time data are then presented. The applicability of the methodology is demonstrated on a maintenance data set from an Australian electricity company.

Brief for GSDR - Emerging Contaminants in urban stormwater: Challenges and perspectives for sustainable water use

Emerging contaminants (ECs) are chemical compounds commonly present in water. It is only recently that this family of compounds is being recognized as significant water pollutants (. ECs include a wide variety of chemicals such as pharmaceutical and personal care products (PPCPs), pesticides, hydrocarbons and hormones, among others, that once released into the environment exert adverse impacts on the human and wildlife endocrine system. Natural attenuation and conventional treatment processes are not capable of removing these micro-pollutants detected in wastewater influent and effluent and surface and drinking water. The main challenges related with presence of ECs in stormwater in the context of reuse are: a) Development of suitable laboratory test methodologies and protocols for ECs identification and quantification b) Identification of the sources of ECs in the urban environment; c) Understanding their impacts on human and/or ecosystem health; and d). Development of cost-effective removal technologies which are appropriate for large as well as small-scale application.

Denitrification losses from an intensively managed sub-tropical pasture: Impact of soil moisture on the partitioning of N2 and N2O emissions

Intensively managed pastures in subtropical Australia under dairy production are nitrogen (N) loaded agro-ecosystems, with an increased pool of N available for denitrification. The magnitude of denitrification losses and N2:N2O partitioning in these agro-ecosystems is largely unknown, representing a major uncertainty when estimating total N loss and replacement. This study investigated the influence of different soil moisture contents on N2 and N2O emissions from a subtropical dairy pasture in Queensland, Australia. Intact soil cores were incubated over 15 days at 80% and 100% water-filled pore space (WFPS), after the application of 15N labelled nitrate, equivalent to 50 kg N ha−1. This setup enabled the direct quantification of N2 and N2O emissions following fertilisation using the 15N gas flux method. The main product of denitrification in both treatments was N2. N2 emissions exceeded N2O emissions by a factor of 8 ± 1 at 80% WFPS and a factor of 17 ± 2 at 100% WFPS. The total amount of N-N2 lost over the incubation period was 21.27 kg ± 2.10 N2-N ha−1 at 80% WFPS and 25.26 kg ± 2.79 kg ha−1 at 100% WFPS respectively. N2 emissions remained high at 100% WFPS, while related N2O emissions decreased. At 80% WFPS, N2 emissions increased constantly over time while N2O fluxes declined. Consequently, N2/(N2 + N2O) product ratios increased over the incubation period in both treatments. N2/(N2 + N2O) product ratios responded significantly to soil moisture, confirming WFPS as a key driver of denitrification. The substantial amount of fertiliser lost as N2 reveals the agronomic significance of denitrification as a major pathway of N loss for sub-tropical pastures at high WFPS and may explain the low fertiliser N use efficiency observed for these agro-ecosystems.

Growth factor-loaded microparticles for tissue engineering: The discrepancies of in vitro characterization assays

Efficient and effective growth factor (GF) delivery is an ongoing challenge for tissue regeneration therapies. The accurate quantification of complex molecules such as GFs, encapsulated in polymeric delivery devices, is equally critical and just as complex as achieving efficient delivery of active GFs. In this study, GFs relevant to bone tissue formation, vascular endothelial growth factor (VEGF) and bone morphogenetic protein 7 (BMP-7), were encapsulated, using the technique of electrospraying, into poly(lactic-co-glycolic acid) microparticles that contained poly(ethylene glycol) and trehalose to assist GF bioactivity. Typical quantification procedures, such as extraction and release assays using saline buffer, generated a significant degree of GF interactions, which impaired accurate assessment by enzyme-linked immunosorbent assay (ELISA). When both dry BMP-7 and VEGF were processed with chloroform, as is the case during the electrospraying process, reduced concentrations of the GFs were detected by ELISA; however, the biological effect on myoblast cells (C2C12) or endothelial cells (HUVECs) was unaffected. When electrosprayed particles containing BMP-7 were cultured with preosteoblasts (MC3T3-E1), significant cell differentiation into osteoblasts was observed up to 3 weeks in culture, as assessed by measuring alkaline phosphatase. In conclusion, this study showed how electrosprayed microparticles ensured efficient delivery of fully active GFs relevant to bone tissue engineering. Critically, it also highlights major discrepancies in quantifying GFs in polymeric microparticle systems when comparing ELISA with cell-based assays.

Autonomous greenhouse gas sampling using multiple robotic boats

Accurately quantifying total greenhouse gas emissions (e.g. methane) from natural systems such as lakes, reservoirs and wetlands requires the spatial-temporal measurement of both diffusive and ebullitive (bubbling) emissions. Traditional, manual, measurement techniques provide only limited localised assessment of methane flux, often introducing significant errors when extrapolated to the whole-of-system. In this paper, we directly address these current sampling limitations and present a novel multiple robotic boat system configured to measure the spatiotemporal release of methane to atmosphere across inland waterways. The system, consisting of multiple networked Autonomous Surface Vehicles (ASVs) and capable of persistent operation, enables scientists to remotely evaluate the performance of sampling and modelling algorithms for real-world process quantification over extended periods of time. This paper provides an overview of the multi-robot sampling system including the vehicle and gas sampling unit design. Experimental results are shown demonstrating the system’s ability to autonomously navigate and implement an exploratory sampling algorithm to measure methane emissions on two inland reservoirs.

Comparison of the sensitivity of different sensor technologies to imbalance severity in low speed wind turbines

Imbalance is not only a direct major cause of downtime in wind turbines, but also accelerates the degradation of neighbouring and downstream components (e.g. main bearing, generator). Along with detection, the imbalance quantification is also essential as some residual imbalance always exist even in a healthy turbine. Three different commonly used sensor technologies (vibration, acoustic emission and electrical measurements) are investigated in this work to verify their sensitivity to different imbalance grades. This study is based on data obtained by experimental tests performed on a small scale wind turbine drive train test-rig for different shaft speeds and imbalance levels. According to the analysis results, electrical measurements seem to be the most suitable for tracking the development of imbalance.