Mathematical investigation of the interactions between the inflammatory response and mechanical aspects of dermal wound repair

Dermal wound repair involves complex interactions between cells, cytokines and mechanics to close injuries to the skin. In particular, we investigate the contribution of fibroblasts, myofibroblasts, TGFβ, collagen and local tissue mechanics to wound repair in the human dermis. We develop a morphoelastic model where a realistic representation of tissue mechanics is key, and a fibrocontractive model that involves a reasonable approximation to the true kinetics of the important bioactive species. We use each of these descriptions to elucidate the mechanisms that generate pathologies such as hypertrophic scars, contractures and keloids. We find that for hypertrophic scar and contracture development, factors regulating the myofibroblast phenotype are critical, with heightened myofibroblast activation, reduced myofibroblast apoptosis or prolonged inflammation all predicted as mediators for scar hypertrophy and contractures. Prevention of these pathologies is predicted when myofibroblast apoptosis is induced, myofibroblast activation is blocked or TGFβ is neutralised. To investigate keloid invasion, we develop a caricature representation of the fibrocontractive model and find that TGFβ spread is the driving factor behind keloid growth. Blocking activation of TGFβ is found to cause keloid regression. Thus, we recommend myofibroblasts and TGFβ as targets for clinicians when developing intervention strategies for prevention and cure of fibrotic scars.

Arm’s length pricing and multinational banks : an old fashioned approach in a modern world

In “Arm’s Length Pricing and Multinational Banks: An Old Fashioned Approach in a Modern World”, Kerrie Sadiq, describes the high level of integration of multinational financial institutions and argues that treating each element within a given operation as a separate entity for transfer pricing purposes is not economically or legally realistic. She proposes instead formulary apportionment as a device for managing this complexity.

A Bayesian regression approach to assess uncertainty in pollutant wash-off modelling

Due to knowledge gaps in relation to urban stormwater quality processes, an in-depth understanding of model uncertainty can enhance decision making. Uncertainty in stormwater quality models can originate from a range of sources such as the complexity of urban rainfall-runoff-stormwater pollutant processes and the paucity of observed data. Unfortunately, studies relating to epistemic uncertainty, which arises from the simplification of reality are limited and often deemed mostly unquantifiable. This paper presents a statistical modelling framework for ascertaining epistemic uncertainty associated with pollutant wash-off under a regression modelling paradigm using Ordinary Least Squares Regression (OLSR) and Weighted Least Squares Regression (WLSR) methods with a Bayesian/Gibbs sampling statistical approach. The study results confirmed that WLSR assuming probability distributed data provides more realistic uncertainty estimates of the observed and predicted wash-off values compared to OLSR modelling. It was also noted that the Bayesian/Gibbs sampling approach is superior compared to the most commonly adopted classical statistical and deterministic approaches commonly used in water quality modelling. The study outcomes confirmed that the predication error associated with wash-off replication is relatively higher due to limited data availability. The uncertainty analysis also highlighted the variability of the wash-off modelling coefficient k as a function of complex physical processes, which is primarily influenced by surface characteristics and rainfall intensity.

From "Secondary Punishment" to "Supermax" : the human costs of high-security regimes in Australia

“Supermax” prisons, conceived by the United States in the early 1980s, are typically reserved for convicted political criminals such as terrorists and spies and for other inmates who are considered to pose a serious ongoing threat to the wider community, to the security of correctional institutions, or to the safety of other inmates. Prisoners are usually restricted to their cells for up to twenty-three hours a day and typically have minimal contact with other inmates and correctional staff. Not only does the Federal Bureau of Prisons operate one of these facilities, but almost every state has either a supermax wing or stand-alone supermax prison. The Globalization of Supermax Prisons examines why nine advanced industrialized countries have adopted the supermax prototype, paying particular attention to the economic, social, and political processes that have affected each state. Featuring essays that look at the U.S.-run prisons of Abu Ghraib and Guantanemo, this collection seeks to determine if the American model is the basis for the establishment of these facilities and considers such issues as the support or opposition to the building of a supermax and why opposition efforts failed; the allegation of human rights abuses within these prisons; and the extent to which the decision to build a supermax was influenced by developments in the United States. Additionally, contributors address such domestic matters as the role of crime rates, media sensationalism, and terrorism in each country’s decision to build a supermax prison.

A nation’s role in addressing base erosion and profit shifting : balancing sovereignty with international collaboration and coordination

The notion of sovereignty is central to any international tax issue. While a nation is free to design its tax laws as it sees fit and raise revenue in accordance with the needs of its citizens, it is not possible to undertake such a task in isolation. In a world of cross-border investments and business transactions, all tax regimes impact on one another. Tax interactions between sovereign states cannot be avoided. Ultimately, the interactions mean that a nation must decide whether to engage in both collaboration and coordination with other nations and supranational bodies alike or maintain an individualised stance in relation to its tax policy. Whatever the decision, there is arguably an exercise in national sovereignty in some form. In the context of an international tax regime, whether that regime is interpreted broadly as meaning international norms generally adopted by nations around the world or domestic regimes legislating for cross-border transactions, rhetoric around national fiscal sovereignty takes on many different forms. At one end of the spectrum it is relied upon by financial secrecy jurisdictions (tax havens) as a defence to their position on the basis that ‘other’ nations cannot interfere with the fiscal sovereignty of a jurisdiction. At the other end of the spectrum, it is argued that profit shifting and international tax avoidance if not stopped is, in and of itself, a threat to a nation’s fiscal sovereignty on the basis that it threatens the ability to tax and raise the revenue needed. This paper considers a modern conceptualisation of sovereignty along with its role within international tax coordination and collaboration to argue that a move towards a more unified approach to addressing international base erosion and profit shifting may be the ultimate exercise of national fiscal sovereignty. By using the current transfer pricing regime as a case study, this paper posits that it is not merely enough to have international agreement on allocation rules to be applied, but that the ultimate exercise of national sovereignty is political agreement with other states to ensure that it is governments which determine the allocational basis of worldwide profits to be taxed. In doing so, it is demonstrated that the arm’s length pricing requirement of the current transfer pricing regime, rather than providing governments with the ability to determine the location of profits, is providing multinational entities with the ultimate power to determine that location. If left unchecked, this will eventually erode a nation’s ability to capture the required tax revenue and, as a consequence, may be deemed a failure by nation states to exercise their fiscal sovereignty.

Sequencing risk : the worst returns in their worst order

For the first of the baby boomers turning 65 years of age, after a decade littered with financial shocks (dot.com bubble, sub-prime, global financial crisis, sovereign debt), sequencing risk can represent a significant threat to their retirement nest eggs. This paper takes an outcomeoriented approach to the problem, to provide practical insights into how sequencing risk works and the critical dependency of retirement outcomes on sequencing risk. Our analysis challenges the conventional wisdom that it is the accumulated average of investment returns that matter. We show, instead, that it is the realised sequence of returns which largely determines the sustainability of retirement incomes.

Former Archbishop of York ‘covered up’ sex abuse scandal

The former Archbishop of York stood accused last night of covering up allegations that a senior Church of England clergyman had abused choirboys and school pupils. Lord Hope of Thornes was made aware of the accusations against the Very Rev Robert Waddington, a former Dean of Manchester Cathedral and once the cleric in overall charge of Church schools, in 1999 and again in 2003. Waddington was stripped of his right to conduct church services but the archbishop did not report concerns about alleged past abuse or a potential continuing threat to children to police or child protection agencies. The extent of Waddington’s alleged history of abuse and the Church’s inaction has been revealed through a joint investigation by The Times and The Australian newspaper in Sydney.

Maximum loadability achievement in SWER networks using optimal sizing and locating of batteries

This paper presents an optimisation algorithm to maximize the loadability of single wire earth return (SWER) by minimizing the cost of batteries and regulators considering the voltage constraints and thermal limits. This algorithm, that finds the optimum location of batteries and regulators, uses hybrid discrete particle swarm optimization and mutation (DPSO + Mutation). The simulation results on realistic highly loaded SWER network show the effectiveness of using battery to improve the loadability of SWER network in a cost-effective way. In this case, while only 61% of peak load can be supplied without violating the constraints by existing network, the loadability of the network is increased to peak load by utilizing two battery sites which are located optimally. That is, in a SWER system like the studied one, each installed kVA of batteries, optimally located, supports a loadability increase as 2 kVA.

The impact of heat waves on children's health : a systematic review

Young children are thought to be particularly sensitive to heatwaves, but relatively less research attention has been paid to this field to date. A systematic review was conducted to elucidate the relationship between heat waves and children’s health. Literature published up to August 2012 were identified using the following MeSH terms and keywords: “heatwave”, “heat wave”, “child health”, “morbidity”, “hospital admission”, “emergency department visit”, “family practice”, “primary health care”, “death” and “mortality”. Of the 628 publications identified, 12 met the selection criteria. The existing literature does not consistently suggest that mortality among children increases significantly during heat waves, even though infants were associated with more heat-related deaths. Exposure to heat waves in the perinatal period may pose a threat to children’s health. Pediatric diseases or conditions associated with heat waves include renal disease, respiratory disease, electrolyte imbalance and fever. Future research should focus on how to develop a consistent definition of a heat wave from a children’s health perspective, identifying the best measure of children’s exposure to heat waves, exploring sensitive outcome measures to quantify the impact of heat waves on children, evaluating the possible impacts of heat waves on children’s birth outcomes, and understanding the differences in vulnerability to heat waves among children of different ages and from different income countries. Projection of the children’s disease burden caused by heat waves under climate change scenarios, and development of effective heat wave mitigation and adaptation strategies that incorporate other child protective health measures, are also strongly recommended.

Distribution harmonic state estimation based on a modified PSO considering parameters uncertainty

This paper presents a new algorithm based on a Modified Particle Swarm Optimization (MPSO) to estimate the harmonic state variables in a distribution networks. The proposed algorithm performs the estimation for both amplitude and phase of each injection harmonic currents by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as the uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WTs). The main features of the proposed MPSO algorithm are usage of a primary and secondary PSO loop and applying the mutation function. The simulation results on 34-bus IEEE radial and a 70-bus realistic radial test networks are presented. The results demonstrate that the speed and the accuracy of the proposed Distribution Harmonic State Estimation (DHSE) algorithm are very excellent compared to the algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO, and Honey Bees Mating Optimization (HBMO).

Distribution harmonic state estimation based on a hybrid PSO and SA algorithm considering parameters uncertainty

This paper presents a new algorithm based on a Hybrid Particle Swarm Optimization (PSO) and Simulated Annealing (SA) called PSO-SA to estimate harmonic state variables in distribution networks. The proposed algorithm performs estimation for both amplitude and phase of each harmonic currents injection by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WT). The main feature of proposed PSO-SA algorithm is to reach quickly around the global optimum by PSO with enabling a mutation function and then to find that optimum by SA searching algorithm. Simulation results on IEEE 34 bus radial and a realistic 70-bus radial test networks are presented to demonstrate the speed and accuracy of proposed Distribution Harmonic State Estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO and Honey Bees Mating Optimization (HBMO) algorithm.

Distribution state estimation based on particle swarm and doubly loop mutant optimization (DLM-PSO)

This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO.

GNSS ambiguity resolution with controllable failure rate for long baseline network RTK

Many large-scale GNSS CORS networks have been deployed around the world to support various commercial and scientific applications. To make use of these networks for real-time kinematic positioning services, one of the major challenges is the ambiguity resolution (AR) over long inter-station baselines in the presence of considerable atmosphere biases. Usually, the widelane ambiguities are fixed first, followed by the procedure of determination of the narrowlane ambiguity integers based on the ionosphere-free model in which the widelane integers are introduced as known quantities. This paper seeks to improve the AR performance over long baseline through efficient procedures for improved float solutions and ambiguity fixing. The contribution is threefold: (1) instead of using the ionosphere-free measurements, the absolute and/or relative ionospheric constraints are introduced in the ionosphere-constrained model to enhance the model strength, thus resulting in the better float solutions; (2) the realistic widelane ambiguity precision is estimated by capturing the multipath effects due to the observation complexity, leading to improvement of reliability of widelane AR; (3) for the narrowlane AR, the partial AR for a subset of ambiguities selected according to the successively increased elevation is applied. For fixing the scalar ambiguity, an error probability controllable rounding method is proposed. The established ionosphere-constrained model can be efficiently solved based on the sequential Kalman filter. It can be either reduced to some special models simply by adjusting the variances of ionospheric constraints, or extended with more parameters and constraints. The presented methodology is tested over seven baselines of around 100 km from USA CORS network. The results show that the new widelane AR scheme can obtain the 99.4 % successful fixing rate with 0.6 % failure rate; while the new rounding method of narrowlane AR can obtain the fix rate of 89 % with failure rate of 0.8 %. In summary, the AR reliability can be efficiently improved with rigorous controllable probability of incorrectly fixed ambiguities.

Cyber crime and its implications to the Pacific

Introduction Cybercrime consists of any criminal action or behaviour that is committed through the use of Information Technology. Common examples of such activities include cyber hacking, identity theft, cracking, spamming, social engineering, data tampering, online fraud, programming attacks, etc. The pervasive use of the internet clearly indicates that the impacts of cybercrime is far reaching and any one, may it be a person or an entity can be a victim of cybercriminal activities. Recently in the US, eight members of a global cybercrime ring were charged in one of the biggest ever bank heists. The cybercrime gang allegedly stole US$45 million by hacking into credit card processing firms and withdrawing money from ATMs in 27 countries (Jessica et al. 2013). An extreme example, the above case highlights how IT is changing the way crimes are being committed. No longer do criminals use masks, guns and get-a-way cars, criminals are able to commit crimes in the comfort of their homes, millions of miles from the scene of the crime and can access significant sums of money that can financially cripple organisations. The world is taking notice of this growing threat and organisations in the Pacific must also be proactive in tackling this emerging issue.

Creation of a new evaluation benchmark for information retrieval targeting patient information needs

Searching for health advice on the web is becoming increasingly common. Because of the great importance of this activity for patients and clinicians and the effect that incorrect information may have on health outcomes, it is critical to present relevant and valuable information to a searcher. Previous evaluation campaigns on health information retrieval (IR) have provided benchmarks that have been widely used to improve health IR and record these improvements. However, in general these benchmarks have targeted the specialised information needs of physicians and other healthcare workers. In this paper, we describe the development of a new collection for evaluation of effectiveness in IR seeking to satisfy the health information needs of patients. Our methodology features a novel way to create statements of patients’ information needs using realistic short queries associated with patient discharge summaries, which provide details of patient disorders. We adopt a scenario where the patient then creates a query to seek information relating to these disorders. Thus, discharge summaries provide us with a means to create contextually driven search statements, since they may include details on the stage of the disease, family history etc. The collection will be used for the first time as part of the ShARe/-CLEF 2013 eHealth Evaluation Lab, which focuses on natural language processing and IR for clinical care.