Thrust allocation with linear constrained quadratic cost function

In this paper, a method of thrust allocation based on a linearly constrained quadratic cost function capable of handling rotating azimuths is presented. The problem formulation accounts for magnitude and rate constraints on both thruster forces and azimuth angles. The advantage of this formulation is that the solution can be found with a finite number of iterations for each time step. Experiments with a model ship are used to validate the thrust allocation system.

Resilience of water supply systems in meeting the challenges posed by climate change and population growth

This research project provides a scientifically robust approach for assessing the resilience of water supply systems, which are critical infrastructure, to impacts of climate change and population growth. An approach for the identification of trigger points that allows timely and appropriate management actions to be taken to avoid catastrophic system failure is an important outcome of this project. In the current absence of a formal method to evaluate the resilience of a water supply system, the approach developed in this study was based on the characterisation of resilience of a water supply system to a range of surrogate measures. Accordingly, a set of indicators are proposed to evaluate system behaviour and logistic regression analysis was used to assess system behaviour under predicted rainfall, storage and demand conditions.

Pathways to peace : a phenomenological exploration of the processes of healing and posttraumatic growth following childhood sexual assault

This thesis explored pathways to healing in men and women who experienced traumatic sexual abuse in childhood and considered themselves to be in a place of wellness. The thesis synthesises current knowledge in this area and has produced a number of models with direct implications for clinical practice. This unique work has also contributed to advancing theoretical understanding of healing following sexual assault.

The effects of geochemical conditions on the establishment and growth of mangrove seedlings in acid sulfate soil environments

Acid sulfate soils (ASS) is a stress factor that is responsible for the failure of some mangrove restoration projects, including abandoned aquaculture ponds converted from mangrove ecosystems. Through experimental and field studies, this research provides a better understanding of the biogeochemistry of ASS disturbance and the response of mangrove seedlings (Rhizophoraceae) under high metal levels and acidic conditions. This study found that mangrove restorations under ASS disturbance can work but with lower numbers of survived seedlings. To prevent toxicity under high levels of metal, seedlings retained metals in their roots and sparingly distributed them into aerial parts with low mobility. The presence of high levels of potential acidity parameters would allow pyrite to oxidise, thus increasing metal levels and acidity, which in turn affected the survival and growth of the seedlings.

kmth price sealed-bid auctions with general independent values and equilibrium linear mark-ups

A generalised bidding model is developed to calculate a bidder’s expected profit and auctioners expected revenue/payment for both a General Independent Value and Independent Private Value (IPV) kmth price sealed-bid auction (where the mth bidder wins at the kth bid payment) using a linear (affine) mark-up function. The Common Value (CV) assumption, and highbid and lowbid symmetric and asymmetric First Price Auctions and Second Price Auctions are included as special cases. The optimal n bidder symmetric analytical results are then provided for the uniform IPV and CV models in equilibrium. Final comments concern implications, the assumptions involved and prospects for further research.

Understanding Uncertainties in Non-Linear Population Trajectories: A Bayesian Semi-Parametric Hierarchical Approach to Large-Scale Surveys of Coral Cover

Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making

Increasing leucine concentration stimulates mechanistic target of rapamycin signaling and cell growth in C2C12 skeletal muscle cells

Leucine is a key amino acid for initiating translation in muscle cells, but the dose-dependent effects of leucine on intracellular signaling are poorly characterized. This study examined the effect that increasing doses of leucine would have on changes in mechanistic target of rapamycin (mTOR)–mediated signaling, rates of protein synthesis, and cell size in C2C12 cells. We hypothesized that a leucine “threshold” exists, which represents the minimum stimulus required to initiate mTOR signaling in muscle cells. Acute exposure to 1.5, 3.2, 5.0, and 16.1 mM leucine increased phosphorylation of mTORSer2448 (~1.4-fold; P < .04), 4E-BP1 Thr37/46 (~1.9-fold; P < .001), and rpS6Ser235/6 (~2.3-fold; P < .001). However, only p70S6kThr389 exhibited a dose-dependent response to leucine with all treatments higher than control (~4-fold; P < .001) and at least 5 mM higher than the 1.5-mM concentration (1.2-fold; P < .02). Rates of protein synthesis were not altered by any treatment. Seven days of exposure to 0.5, 1.5, 5.0, and 16.5 mM leucine resulted in an increase in cell size in at least 5 mM treatments (~1.6-fold, P < .001 vs control). Our findings indicate that even at low leucine concentrations, phosphorylation of proteins regulating translation initiation signaling is enhanced. The phosphorylation of p70S6kThr389 follows a leucine dose-response relationship, although this was not reflected by the acute protein synthetic response. Nevertheless, under the conditions of the present study, it appears that leucine concentrations of at least 5 mM are necessary to enhance cell growth.

Identifying weak linear features with the "coalescing shortest path image transform"

The detection of line-like features in images finds many applications in microanalysis. Actin fibers, microtubules, neurites, pilis, DNA, and other biological structures all come up as tenuous curved lines in microscopy images. A reliable tracing method that preserves the integrity and details of these structures is particularly important for quantitative analyses. We have developed a new image transform called the "Coalescing Shortest Path Image Transform" with very encouraging properties. Our scheme efficiently combines information from an extensive collection of shortest paths in the image to delineate even very weak linear features. © Copyright Microscopy Society of America 2011.

Models of protein linear molecular motors for dynamic nanodevices

Protein molecular motors are natural nano-machines that convert the chemical energy from the hydrolysis of adenosine triphosphate into mechanical work. These efficient machines are central to many biological processes, including cellular motion, muscle contraction and cell division. The remarkable energetic efficiency of the protein molecular motors coupled with their nano-scale has prompted an increasing number of studies focusing on their integration in hybrid micro- and nanodevices, in particular using linear molecular motors. The translation of these tentative devices into technologically and economically feasible ones requires an engineering, design-orientated approach based on a structured formalism, preferably mathematical. This contribution reviews the present state of the art in the modelling of protein linear molecular motors, as relevant to the future design-orientated development of hybrid dynamic nanodevices. © 2009 The Royal Society of Chemistry.

Evidence for a simple linear relationship between MRSA rates and hand-washing compliance [Comment]

Is there a threshold above which hand-rub solution consumption is efficient for decreasing MRSA incidence? [J Hosp Infect. 2009] Association between an index of consumption of hand-rub solution and the incidence of acquired meticillin-resistant Staphylococcus aureus in an intensive care unit.

Microalgal growth characteristics and subsequent influence on dewatering efficiency

Dewatering of microalgal culture is a major bottleneck towards the industrial-scale processing of microalgae for bio-diesel production. The dilute nature of harvested microalgal cultures poses a huge operation cost to dewater; thereby rendering microalgae-based fuels less economically attractive. This study explores the influence of microalgal growth phases and intercellular interactions during cultivation on dewatering efficiency of microalgae cultures. Experimental results show that microalgal cultures harvested during a low growth rate phase (LGRP) of 0.03 d-1 allowed a higher rate of settling than those harvested during a high growth rate phase (HGRP) of 0.11 d-1, even though the latter displayed a higher average differential biomass concentration of 0.2 g L-1 d-1. Zeta potential profile during the cultivation process showed a maximum electronegative value of -43.2 ± 0.7 mV during the HGRP which declined to stabilization at -34.5 ± 0.4 mV in the LGRP. The lower settling rate observed for HGRP microalgae is hence attributed to the high stability of the microalgal cells which electrostatically repel each other during this growth phase. Tangential flow filtration of 20 L HGRP culture concentrated 23 times by consuming 0.51 kWh/m3 of supernatant removed whilst 0.38 kWh/m3 was consumed to concentrate 20 L of LGRP by 48 times.