Foundations of International Climate Law : Objectives, principles and methods

This chapter explores the objectives, principle and methods of climate law. The United Nations Framework Convention on Climate Change (UNFCCC) lays the foundations of the international regime by setting out its ultimate objectives in Article 2, the key principles in Article 3, and the methods of the regime in Article 4. The ultimate objective of the regime – to avoid dangerous anthropogenic interference – is examined and assessments of the Intergovernmental Panel on Climate Change (IPCC) are considered when seeking to understand the definition of this concept. The international environmental principles of: state sovereignty and responsibility, preventative action, cooperation, sustainable development, precaution, polluter pays and common but differentiated responsibility are then examined and their incorporation within the international climate regime instruments evaluated. This is followed by an examination of the methods used by the mitigation and adaptation regimes in seeking to achieve the objective of the UNFCCC. Methods of the mitigation regime include: domestic implementation of policies, setting of standards and targets and allocation of rights, use of flexibility mechanisms, and reporting. While it is noted that methods of the adaptation regime are still evolving, the latter includes measures such as impact assessments, national adaptation plans and the provision of funding.

Screening and managing cannabis use: comparing GP's and nurses' knowledge, beliefs, and behavior

Background: General practitioners (GPs) and nurses are ideally placed to address the significant unmet demand for the treatment of cannabis-related problems given the numbers of people who regularly seek their care. The aim of this study was to evaluate differences between GPs and nurses’ perceived knowledge, beliefs, and behaviors toward cannabis use and its screening and management. Methods: This study involved 161 nurses and 503 GPs who completed a survey distributed via conference satchels to delegates of Healthed seminars focused on topics relevant to women and children’s health. Differences between GPs and nurses were analyzed using χ2- tests and two-sample t-tests, while logistic regression examined predictors of service provision. Results: GPs were more likely than nurses to have engaged in cannabis-related service provision, but also more frequently reported barriers related to time, interest, and having more important issues to address. Nurses reported less knowledge, skills, and role legitimacy. Perceived screening skills predicted screening and referral to alcohol and other drug (AOD) services, while knowing a regular user increased the likelihood of referrals only. Conclusions: Approaches to increase cannabis-related screening and intervention may be improved by involving nurses, and by leveraging the relationship between nurses and doctors, in primary care.

Review of statistical methods for disease mapping

Cancer poses an undeniable burden to the health and wellbeing of the Australian community. In a recent report commissioned by the Australian Institute for Health and Welfare(AIHW, 2010), one in every two Australians on average will be diagnosed with cancer by the age of 85, making cancer the second leading cause of death in 2007, preceded only by cardiovascular disease. Despite modest decreases in standardised combined cancer mortality over the past few decades, in part due to increased funding and access to screening programs, cancer remains a significant economic burden. In 2010, all cancers accounted for an estimated 19% of the country's total burden of disease, equating to approximately $3:8 billion in direct health system costs (Cancer Council Australia, 2011). Furthermore, there remains established socio-economic and other demographic inequalities in cancer incidence and survival, for example, by indigenous status and rurality. Therefore, in the interests of the nation's health and economic management, there is an immediate need to devise data-driven strategies to not only understand the socio-economic drivers of cancer but also facilitate the implementation of cost-effective resource allocation for cancer management...

Upper-body morbidity after breast cancer : incidence and evidence for evaluation, prevention, and management within a prospective surveillance model of care

The purpose of this paper is to review the incidence of upper-body morbidity (arm and breast symptoms, impairments, and lymphedema), methods for diagnosis, and prevention and treatment strategies. It was also the purpose to highlight the evidence base for integration of prospective surveillance for upper-body morbidity within standard clinical care of women with breast cancer. Between 10% and 64% of women report upper-body symptoms between 6 months and 3 years after breast cancer, and approximately 20% develop lymphedema. Symptoms remain common into longer-term survivorship, and although lymphedema may be transient for some, those who present with mild lymphedema are at increased risk of developing moderate to severe lymphedema. The etiology of morbidity seems to be multifactorial, with the most consistent risk factors being those associated with extent of treatment. However, known risk factors cannot reliably distinguish between those who will and will not develop upper-body morbidity. Upper-body morbidity may be treatable with physical therapy. There is also evidence in support of integrating regular surveillance for upper-body morbidity into the routine care provided to women with breast cancer, with early diagnosis potentially contributing to more effective management and prevention of progression of these conditions.

The effect of injury diagnosis on expected Postconcussion Syndrome (PCS) symptom reporting and illness perception

Objective: To determine if systematic variation of diagnostic terminology (i.e. concussion, minor head injury [MHI], mild traumatic brain injury [mTBI]) following a standardized injury description produced different expected symptoms and illness perceptions. We hypothesized that worse outcomes would be expected of mTBI, compared to other diagnoses, and that MHI would be perceived as worse than concussion. Method:108 volunteers were randomly allocated to conditions in which they read a vignette describing a motor vehicle accident-related mTBI followed by: a diagnosis of mTBI (n=27), MHI (n=24), concussion (n=31); or, no diagnosis (n=26). All groups rated: a) event ‘undesirability’; b) illness perception, and; c) expected Postconcussion Syndrome (PCS) and Posttraumatic Stress Disorder (PTSD) symptoms six months post injury. Results: On average, more PCS symptomatology was expected following mTBI compared to other diagnoses, but this difference was not statistically significant. There was a statistically significant group effect on undesirability (mTBI>concussion & MHI), PTSD symptomatology (mTBI & no diagnosis>concussion), and negative illness perception (mTBI & no diagnosis>concussion). Conclusion: In general, diagnostic terminology did not affect anticipated PCS symptoms six months post injury, but other outcomes were affected. Given that these diagnostic terms are used interchangeably, this study suggests that changing terminology can influence known contributors to poor mTBI outcome.

Guerrilla research tactics: alternative research methods

This case-study explores alternative and experimental methods of research data acquisition, through an emerging research methodology, ‘Guerrilla Research Tactics’ [GRT]. The premise is that the researcher develops covert tactics for attracting and engaging with research participants. These methods range between simple analogue interventions to physical bespoke artefacts which contain an embedded digital link to a live, interactive data collecting resource, such as an online poll, survey or similar. These artefacts are purposefully placed in environments where the researcher anticipates an encounter and response from the potential research participant. The choice of design and placement of artefacts is specific and intentional. DESCRIPTION: Additional information may include: the outcomes; key factors or principles that contribute to its effectiveness; anticipated impact/evidence of impact. This case-study assesses the application of ‘Guerrilla Research Tactics’ [GRT] Methodology as an alternative, engaging and interactive method of data acquisition for higher degree research. Extending Gauntlett’s definition of ‘new creative methods… an alternative to language driven qualitative research methods' (2007), this case-study contributes to the existing body of literature addressing creative and interactive approaches to HDR data collection. The case-study was undertaken with Masters of Architecture and Urban Design research students at QUT, in 2012. Typically students within these creative disciplines view research as a taxing and boring process, distracting them from their studio design focus. An obstacle that many students face, is acquiring data from their intended participant groups. In response to these challenges the authors worked with students to develop creative, fun, and engaging research methods for both the students and their research participants. GRT are influenced by and developed from a combination of participatory action research (Kindon, 2008) and unobtrusive research methods (Kellehear, 1993), to enhance social research. GRT takes un-obtrusive research in a new direction, beyond the typical social research methods. The Masters research students developed alternative methods for acquiring data, which relied on a combination of analogue design interventions and online platforms commonly distributed through social networks. They identified critical issues that required action by the community, and the processes they developed focused on engaging with communities, to propose solutions. Key characteristics shared between both GRT and Guerrilla Activism, are notions of political issues, the unexpected, the unconventional, and being interactive, unique and thought provoking. The trend of Guerrilla Activism has been adapted to: marketing, communication, gardening, craftivism, theatre, poetry, and art. Focusing on the action element and examining elements of current trends within Guerrilla marketing, we believe that GRT can be applied to a range of research areas within various academic disciplines.

A spectroscopic comparison of YBCO superconductors synthesised by solid-state and co-precipitation methods

Raman spectroscopy, X-ray diffraction (XRD), and scanning electron microscopy (SEM) have been used to compare samples of YBa2Cu3O7 (YBCO) synthesised by the solid-state method and a novel co-precipitation technique. XRD results indicate that YBCO prepared by these two methods are phase pure, however the Raman and SEM results show marked differences between these samples.

Numerical methods for strong solutions of stochastic differential equations : an overview

This paper gives a review of recent progress in the design of numerical methods for computing the trajectories (sample paths) of solutions to stochastic differential equations. We give a brief survey of the area focusing on a number of application areas where approximations to strong solutions are important, with a particular focus on computational biology applications, and give the necessary analytical tools for understanding some of the important concepts associated with stochastic processes. We present the stochastic Taylor series expansion as the fundamental mechanism for constructing effective numerical methods, give general results that relate local and global order of convergence and mention the Magnus expansion as a mechanism for designing methods that preserve the underlying structure of the problem. We also present various classes of explicit and implicit methods for strong solutions, based on the underlying structure of the problem. Finally, we discuss implementation issues relating to maintaining the Brownian path, efficient simulation of stochastic integrals and variable-step-size implementations based on various types of control.

High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations

The pioneering work of Runge and Kutta a hundred years ago has ultimately led to suites of sophisticated numerical methods suitable for solving complex systems of deterministic ordinary differential equations. However, in many modelling situations, the appropriate representation is a stochastic differential equation and here numerical methods are much less sophisticated. In this paper a very general class of stochastic Runge-Kutta methods is presented and much more efficient classes of explicit methods than previous extant methods are constructed. In particular, a method of strong order 2 with a deterministic component based on the classical Runge-Kutta method is constructed and some numerical results are presented to demonstrate the efficacy of this approach.

Order conditions of stochastic Runge-Kutta methods by B-series

In this paper, general order conditions and a global convergence proof are given for stochastic Runge Kutta methods applied to stochastic ordinary differential equations ( SODEs) of Stratonovich type. This work generalizes the ideas of B-series as applied to deterministic ordinary differential equations (ODEs) to the stochastic case and allows a completely general formalism for constructing high order stochastic methods, either explicit or implicit. Some numerical results will be given to illustrate this theory.

Adams-Type Methods for the Numerical Solution of Stochastic Ordinary Differential Equations

Stochastic differential equations (SDEs) arise fi om physical systems where the parameters describing the system can only be estimated or are subject to noise. There has been much work done recently on developing numerical methods for solving SDEs. This paper will focus on stability issues and variable stepsize implementation techniques for numerically solving SDEs effectively. (C) 2000 Elsevier Science B.V. All rights reserved.

High strong order methods for non-commutative stochastic ordinary differential equation systems and the Magnus formula

In recent years considerable attention has been paid to the numerical solution of stochastic ordinary differential equations (SODEs), as SODEs are often more appropriate than their deterministic counterparts in many modelling situations. However, unlike the deterministic case numerical methods for SODEs are considerably less sophisticated due to the difficulty in representing the (possibly large number of) random variable approximations to the stochastic integrals. Although Burrage and Burrage [High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations, Applied Numerical Mathematics 22 (1996) 81-101] were able to construct strong local order 1.5 stochastic Runge-Kutta methods for certain cases, it is known that all extant stochastic Runge-Kutta methods suffer an order reduction down to strong order 0.5 if there is non-commutativity between the functions associated with the multiple Wiener processes. This order reduction down to that of the Euler-Maruyama method imposes severe difficulties in obtaining meaningful solutions in a reasonable time frame and this paper attempts to circumvent these difficulties by some new techniques. An additional difficulty in solving SODEs arises even in the Linear case since it is not possible to write the solution analytically in terms of matrix exponentials unless there is a commutativity property between the functions associated with the multiple Wiener processes. Thus in this present paper first the work of Magnus [On the exponential solution of differential equations for a linear operator, Communications on Pure and Applied Mathematics 7 (1954) 649-673] (applied to deterministic non-commutative Linear problems) will be applied to non-commutative linear SODEs and methods of strong order 1.5 for arbitrary, linear, non-commutative SODE systems will be constructed - hence giving an accurate approximation to the general linear problem. Secondly, for general nonlinear non-commutative systems with an arbitrary number (d) of Wiener processes it is shown that strong local order I Runge-Kutta methods with d + 1 stages can be constructed by evaluated a set of Lie brackets as well as the standard function evaluations. A method is then constructed which can be efficiently implemented in a parallel environment for this arbitrary number of Wiener processes. Finally some numerical results are presented which illustrate the efficacy of these approaches. (C) 1999 Elsevier Science B.V. All rights reserved.