A way forward for land-use planning to achieve policy goals by using spatial modelling scenarios

This paper investigates how demographic (socioeconomic) and land-use (physical and environmental) data can be integrated within a decision support framework to formulate and evaluate land-use planning scenarios. A case-study approach is undertaken with land-use planning scenarios for a rapidly growing coastal area in Australia, the Shire of Hervey Bay. The town and surrounding area require careful planning of the future urban growth between competing land uses. Three potential urban growth scenarios are put forth to address this issue. Scenario A ('continued growth') is based on existing socioeconomic trends. Scenario B ('maximising rates base') is derived using optimisation modelling of land-valuation data. Scenario C ('sustainable development') is derived using a number of social, economic, and environmental factors and assigning weightings of importance to each factor using a multiple criteria analysis approach. The land-use planning scenarios are presented through the use of maps and tables within a geographical information system, which delineate future possible land-use allocations up until 2021. The planning scenarios are evaluated by using a goal-achievement matrix approach. The matrix is constructed with a number of criteria derived from key policy objectives outlined in the regional growth management framework and town planning schemes. The authors of this paper examine the final efficiency scores calculated for each of the three planning scenarios and discuss the advantages and disadvantages of the three land-use modelling approaches used to formulate the final scenarios.

Meaning-based quality-of-life measurement: A way forward in conceptualizing and measuring client outcomes?

Despite current imperatives to measure client outcomes, social workers have expressed frustration with the ability of traditional forms of quantitative methods to engage with complexity, individuality and meaning. This paper argues that the inclusion of a meaning-based as opposed to a function-based approach to quality of life (QOL) may offer a quantitative means of measurement that is congruent with social-work values and practice.

Inhibitors of cholesteryl ester transfer protein - a step forward in the treatment of coronary artery disease?

Although the LDL cholesterol-lowering statins have reduced the mortality and morbidity associated with coronary artery disease (CAD), considerable mortality and morbidity remains. Increasing HDL cholesterol levels is associated with reduced CAD mortality and morbidity. In healthy subjects with mild dyslipidemia, treatment with JTT-705 decreased cholesteryl ester transfer protein (CETP) activity, increased HDL cholesterol and decreased LDL cholesterol. Similarly, another CETP inhibitor, torcetrapib, has recently been shown to increase HDL cholesterol by 46%, decrease LDL cholesterol by 8% and have no effect on triglycerides in subjects with HDL cholesterol levels below 1.0 mmol/l. Increasing HDL cholesterol with inhibitors of CETP represents a new approach to dyslipidemia that requires further investigation, especially in patients with CAD.

Referral patterns in a global store-and-forward telemedicine system

We examined the nature of the referral patterns in the email telemedicine network operated by the Swinfen Charitable Trust with a view to informing long-term resource planning. Over the first six years of operation, 62 hospitals from 19 countries registered with the Trust in order to be able to refer cases for specialist advice; 55 of these hospitals (89%) actually referred cases during this period. During the first six years of operation, nearly 1000 referrals were submitted and answered, from a wide range of specialty areas. Between July 2002 and March 2005 the referral rate rose from 127 to 318 cases per year. The median length of time required to provide a specialist's response was 2.3 days during the first 12 months and 1.8 days during the last 12 months. Five hospitals submitted cases for more than four years (together sending a total of 493 cases). Their activity data showed a trend to declining referral rates over the four-year period, which may represent successful knowledge transfer. There is some evidence that over the last three years the growth in demand has been exponential, while the growth in resources available (i.e. specialists) has been linear, a situation which cannot continue for very long before demand outstrips supply.

The Australian insolvency regime revisited: a precis of the next leap forward

Australian corporate insolvency laws contained within Chapter 5 of the Corporations Act are currently being reviewed with respect to four principal areas identified by Australian Government Treasury. The four themes of review include employee ‘benefit’ enhancements; seeking to deter misconduct of company officers; rules around insolvency practitioner disclosure with respect to their remuneration and related independence issues; and some minor proposed changes to the voluntary administration procedure, widely regarded as requiring only minor adjustment. At this time, the draft legislation is not available for general release and is being discussed within the Australian Government appointed Insolvency Law Advisory Group. The next steps are public comment for review of draft legislation and then operation of the legislative change. These are expected to occur in 2007. This paper seeks to outline the likely issues associated with the expected reforms of the Australian insolvency regime.

Tracking the states of a nonlinear system in the weight-space of a feed-forward neural network

Nonlinear, non-stationary signals are commonly found in a variety of disciplines such as biology, medicine, geology and financial modeling. The complexity (e.g. nonlinearity and non-stationarity) of such signals and their low signal to noise ratios often make it a challenging task to use them in critical applications. In this paper we propose a new neural network based technique to address those problems. We show that a feed forward, multi-layered neural network can conveniently capture the states of a nonlinear system in its connection weight-space, after a process of supervised training. The performance of the proposed method is investigated via computer simulations.