Regional trade-offs between mine water and energy use : a water treatment case study

The mining industry faces concurrent pressures of reducing water use, energy consumption and greenhouse gas (GHG) emissions in coming years. However, the interactions between water and energy use, as well as GHG e missions have largely been neglected in modelling studies to date. In addition, investigations tend to focus on the unit operation scale, with little consideration of whole-of-site or regional scale effects. This paper presents an application of a hierarchical systems model (HSM) developed to represent water, energy and GHG emissions fluxes at scales ranging from the unit operation, to the site level, to the regional level. The model allows for the linkages between water use, energy use and GHG emissions to be examined in a fl exible and intuitive way, so that mine sites can predict energy and emissions impacts of water use reduction schemes and vice versa. This paper examines whether this approach can also be applied to the regional scale with multiple mine sites. The model is used to conduct a case study of several coal mines in the Bowen Basin, Australia, to compare the utility of centralised and decentralised mine water treatment schemes. The case study takes into account geographical factors (such as water pumping distances and elevations), economic factors (such as capital and operating cost curves for desalination treatment plants) and regional factors (such as regionally varying climates and associated variance in mine water volumes and quality). The case study results indicate that treatment of saline mine water incurs a trade-off between water and energy use in all cases. However, significant cost differences between centralised and decentralised schemes can be observed in a simple economic analysis. Further research will examine the possibility for deriving model up-scaling algorithms to reduce computational requirements.

Twisted Edwards curves revisited

This paper introduces fast algorithms for performing group operations on twisted Edwards curves, pushing the recent speed limits of Elliptic Curve Cryptography (ECC) forward in a wide range of applications. Notably, the new addition algorithm uses for suitably selected curve constants. In comparison, the fastest point addition algorithms for (twisted) Edwards curves stated in the literature use . It is also shown that the new addition algorithm can be implemented with four processors dropping the effective cost to . This implies an effective speed increase by the full factor of 4 over the sequential case. Our results allow faster implementation of elliptic curve scalar multiplication. In addition, the new point addition algorithm can be used to provide a natural protection from side channel attacks based on simple power analysis (SPA).

Faster group operations on elliptic curves

This paper improves implementation techniques of Elliptic Curve Cryptography. We introduce new formulae and algorithms for the group law on Jacobi quartic, Jacobi intersection, Edwards, and Hessian curves. The proposed formulae and algorithms can save time in suitable point representations. To support our claims, a cost comparison is made with classic scalar multiplication algorithms using previous and current operation counts. Most notably, the best speeds are obtained from Jacobi quartic curves which provide the fastest timings for most scalar multiplication strategies benefiting from the proposed 12M + 5S + 1D point doubling and 7M + 3S + 1D point addition algorithms. Furthermore, the new addition algorithm provides an efficient way to protect against side channel attacks which are based on simple power analysis (SPA). Keywords: Efficient elliptic curve arithmetic,unified addition, side channel attack.

Applying data mining to assess crash risk on curves

The wide range of contributing factors and circumstances surrounding crashes on road curves suggest that no single intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify contributing factors and the relationship between them. It identifies contributing factors that influence the risk of a crash. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set theory was used to discover dependencies among data, and reasons using the vague, uncertain and imprecise information that characterised the insurance dataset. The results show that male drivers, who are between 50 and 59 years old, driving during evening peak hours are involved with a collision, had a lowest crash risk. Drivers between 25 and 29 years old, driving from around midnight to 6 am and in a new car has the highest risk. The analysis of the most significant contributing factors on curves suggests that drivers with driving experience of 25 to 42 years, who are driving a new vehicle have the highest crash cost risk, characterised by the vehicle running off the road and hitting a tree. This research complements existing statistically based tools approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to designing tailored countermeasures.

Thoracoscopic scoliosis surgery – a cheaper option? A cost analysis of 189 consecutive cases

INTRODUCTION: Increasing health care costs, limited resources and increased demand makes cost effective and cost-efficient delivery of Adolescent Idiopathic Scoliosis (AIS) management paramount. Rising implant costs in deformity correction surgery have prompted analysis of whether high implant densities are justified. The objective of this study was to analyse the costs of thoracoscopic scoliosis surgery, comparing initial learning curve costs with those of the established technique and to the costs involved in posterior instrumented fusion from the literature. METHODS: 189 consecutive cases from April 2000 to July 2011 were assessed with a minimum of 2 years follow-up. Information was gathered from a prospective database covering perioperative factors, clinical and radiological outcomes, complications and patient reported outcomes. The patients were divided into three groups to allow comparison; 1. A learning curve cohort, 2. An intermediate cohort and 3. A third cohort of patients, using our established technique. Hospital finance records and implant manufacturer figures were corrected to 2013 costs. A literature review of AIS management costs and implant density in similar curve types was performed. RESULTS: The mean pre-op Cobb angle was 53°(95%CI 0.4) and was corrected postop to mean 22.9°(CI 0.4). The overall complication rate was 20.6%, primarily in the first cohort, with a rate of 5.6% in the third cohort. The average total costs were $46,732, operating room costs of $10,301 (22.0%) and ICU costs of $4620 (9.8%). The mean number of screws placed was 7.1 (CI 0.04) with a single rod used for each case giving average implant costs of $14,004 (29.9%). Comparison of the three groups revealed higher implant costs as the technique evolved to that in use today, from $13,049 in Group 1 to $14577 in Group 3 (P<0.001). Conversely operating room costs reduced from $10,621 in Group 1 to $7573 (P<0.001) in Group 3. ICU stay was reduced from an average of 1.2 to 0 days. In-patient stay was significantly (P=0.006) lower in Groups 2 and 3 (5.4 days) than Group 1 (5.9 days) (i.e. a reduction in cost of approximately $6,140). CONCLUSIONS: The evolution of our thoracoscopic anterior scoliosis correction has resulted in an increase in the number of levels fused and reduction in complication rate. Implant costs have risen as a result, however, there has been a concurrent decrease in those costs generated by operating room use, ICU and in-patient stay with increasing experience. Literature review of equivalent curve types treated posteriorly shows similar perioperative factors but higher implant density, 69-83% compared to the 50% in this study. Thoracoscopic Scoliosis surgery presents a low density, reliable, efficient and effective option for selected curves. A cost analysis of Thoracoscopic Scoliosis Surgery using financial records and a prospectively collected database of all patients since 2000, demonstrating a clear cost advantage compared to equivalent posterior instrumentation and fusion.

Reducing the global burden of depression : population level analysis of intervention cost-effectiveness in 14 world regions

International evidence on the cost and effects of interventions for reducing the global burden of depression remain scarce. Aims: To estimate the population-level cost-effectiveness of evidence-based depression interventions and their contribution towards reducing current burden. Method: Primary-care-based depression interventions were modelled at the level of whole populations in 14 epidemiological subregions of the world. Total population-level costs (in international dollars or I$) and effectiveness (disability adjusted life years (DALYs) averted) were combined to form average and incremental cost-effectiveness ratios. Results: Evaluated interventions have the potential to reduce the current burden of depression by 10–30%. Pharmacotherapy with older antidepressant drugs, with or without proactive collaborative care, are currently more cost-effective strategies than those using newer antidepressants, particularly in lower-income subregions. Conclusions: Even in resource-poor regions, each DALYaverted by efficient depression treatments in primary care costs less than 1 year of average per capita income, making such interventions a cost-effective use of health resources. However, current levels of burden can only be reduced significantlyif there is a substantialincrease substantial increase intreatment coverage.

Correcting for bias when estimating the cost of hospital-acquired infection : an analysis of lower respiratory tract infections in non-surgical patients

Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).