A new public health context to understand male sex work

Background Researching male sex work offers insight into the sexual lives of men and women while developing a more realistic appreciation for the changing issues associated with male sex work. This type of research is important because it not only reflects a growing and diversifying consumer demand for male sex work, but also because it enables the construction of knowledge that is up-to-date with changing ideas around sex and sexualities. Discussion This paper discusses a range of issues emerging in the male sex industry. Notably, globalisation and technology have contributed to the normalisation of male sex work and reshaped the landscape in which the male sex industry operates. As part of this discussion, we review STI and HIV rates among male sex workers at a global level, which are widely disparate and geographically contextual, with rates of HIV among male sex workers ranging from 0% in some areas to 50% in others. The Internet has reshaped the way that male sex workers and clients connect and has been identified as a useful space for safer sex messages and research that seeks out hidden or commonly excluded populations. Future directions We argue for a public health context that recognises the emerging and changing nature of male sex work, which means programs and policies that are appropriate for this population group. Online communities relating to male sex work are important avenues for safer sexual messages and unique opportunities to reach often excluded sub-populations of both clients and male sex workers. The changing structure and organisation of male sex work alongside rapidly changing cultural, academic and medical discourses provide new insight but also new challenges to how we conceive the sexualities of men and male sex workers. Public health initiatives must reflect upon and incorporate this knowledge.

The Australia-Chile free trade agreement 2008: Intellectual property and development. A submission to the Joint Standing Committee on treaties

A submission to the Joint Standing Committee on treaties

New graph-based algorithms to efficiently solve large scale open pit mining optimisation problems

In the mining optimisation literature, most researchers focused on two strategic-level and tactical-level open-pit mine optimisation problems, which are respectively termed ultimate pit limit (UPIT) or constrained pit limit (CPIT). However, many researchers indicate that the substantial numbers of variables and constraints in real-world instances (e.g., with 50-1000 thousand blocks) make the CPIT’s mixed integer programming (MIP) model intractable for use. Thus, it becomes a considerable challenge to solve the large scale CPIT instances without relying on exact MIP optimiser as well as the complicated MIP relaxation/decomposition methods. To take this challenge, two new graph-based algorithms based on network flow graph and conjunctive graph theory are developed by taking advantage of problem properties. The performance of our proposed algorithms is validated by testing recent large scale benchmark UPIT and CPIT instances’ datasets of MineLib in 2013. In comparison to best known results from MineLib, it is shown that the proposed algorithms outperform other CPIT solution approaches existing in the literature. The proposed graph-based algorithms leads to a more competent mine scheduling optimisation expert system because the third-party MIP optimiser is no longer indispensable and random neighbourhood search is not necessary.

Genome-wide study of familial juvenile hyperuricaemic (gouty) nephropathy (FJHN) indicates a new locus, FJHN3, linked to chromosome 2p22.1-p21

Familial juvenile hyperuricaemic (gouty) nephropathy (FJHN), is an autosomal dominant disease associated with a reduced fractional excretion of urate, and progressive renal failure. FJHN is genetically heterogeneous and due to mutations of three genes: uromodulin (UMOD), renin (REN) and hepatocyte nuclear factor-1beta (HNF-1β) on chromosomes 16p12, 1q32.1, and 17q12, respectively. However, UMOD, REN or HNF-1β mutations are found in only ~45% of FJHN probands, indicating the involvement of other genetic loci in ~55% of probands. To identify other FJHN loci, we performed a single nucleotide polymorphism (SNP)-based genome-wide linkage analysis, in six FJHN families in whom UMOD, HNF-1β and REN mutations had been excluded. Parametric linkage analysis using a 'rare dominant' model established linkage in five of the six FJHN families, with a LOD score >+3, at 0% recombination, between FJHN and SNPs at chromosome 2p22.1-p21. Analysis of individual recombinants in two unrelated affected individuals defined a ~5.5 Mbp interval, flanked telomerically by SNP RS372139 and centromerically by RS896986 that contained the locus, designated FJHN3. The interval contains 28 genes, and DNA sequence analysis of the most likely candidate, solute carrier family 8 member 1 (SLC8A1), did not identify any abnormalities in the FJHN3 probands. FJHN3 is likely located within a ~5.5 Mbp interval on chromosome 2p22.1-p21, and identifying the genetic abnormality will help to further elucidate mechanisms predisposing to gout and renal failure.

A new multi-objective model to optimise rail transport scheduler

The sugarcane transport system plays a critical role in the overall performance of Australia’s sugarcane industry. An inefficient sugarcane transport system interrupts the raw sugarcane harvesting process, delays the delivery of sugarcane to the mill, deteriorates the sugar quality, increases the usage of empty bins, and leads to the additional sugarcane production costs. Due to these negative effects, there is an urgent need for an efficient sugarcane transport schedule that should be developed by the rail schedulers. In this study, a multi-objective model using mixed integer programming (MIP) is developed to produce an industry-oriented scheduling optimiser for sugarcane rail transport system. The exact MIP solver (IBM ILOG-CPLEX) is applied to minimise the makespan and the total operating time as multi-objective functions. Moreover, the so-called Siding neighbourhood search (SNS) algorithm is developed and integrated with Sidings Satisfaction Priorities (SSP) and Rail Conflict Elimination (RCE) algorithms to solve the problem in a more efficient way. In implementation, the sugarcane transport system of Kalamia Sugar Mill that is a coastal locality about 1050 km northwest of Brisbane city is investigated as a real case study. Computational experiments indicate that high-quality solutions are obtainable in industry-scale applications.